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**A**: For the random sampling strategy, ref. [14] proposes a variable density probabilistic sampling strategy for smooth graph signals.
**B**: The sampling strategies for graph signals generally include deterministic and random sampling strategies**C**: Currently, deterministic sampling strategies are mainly studied u... | ABC | CAB | CBA | CBA | Selection 2 |
**A**: Therefore, we employ the mask of the annotated modality, dilating it to ensure adequate coverage of the tumor across various modalities. Subsequently, this mask is utilized in the Normal CT Generator (NCG) module for inpainting, yielding the normal CT**B**: Within the latent space, the Multimodal CT Synthesizer ... | CBA | BCA | ACB | BAC | Selection 2 |
**A**: The MCAM module uses dual multi-scale visual features to generate noise with multi-frequency spatial correlations that match real noise. Additionally, our nearly lossless accelerated sampling method, DIPS, is tailored for synthetic noise tasks. Our approach achieves state-of-the-art performance across multiple b... | ACB | CAB | ABC | ABC | Selection 2 |
**A**: They are respectively composed of 17 and 69 images, which usually are used to evaluate the generalization ability of enhancement algorithms. For unpaired datasets, we introduce a no-reference evaluator NIQE [38] to assess their performance.**B**: MEF [35] and DICM [25] are two unpaired datasets without refere... | CAB | ACB | ABC | CBA | Selection 4 |
**A**: Following that, the neural network is built and trained using MATLAB’s graphical user interfaces (GUIs) intended exclusively for neural network (NN) applications. After the dataset has been built within the MATLAB workspace, these GUIs make it easier to create and train the neural network. To improve the perform... | CAB | BCA | BAC | ACB | Selection 2 |
**A**: Considering a 0.5 cycle (64 samples) the proposed method can trip all faults within ∼similar-to\sim∼10.6ms for single-end and within ∼similar-to\sim∼17.5ms for double-end measurements (with communication time delay) which is comparable to the aforementioned methods. Intel Core i5-9500 CPU @ 3.0 GHz and 16 GB RAM... | CAB | CBA | ACB | BAC | Selection 1 |
**A**: This balance between anatomical alignment and realistic signal decay is crucial for accurate IVIM parameter estimation, highlighting IVIM-Morph’s effectiveness in maintaining signal integrity alongside reasonable anatomical registration.
**B**: Although IVIM-Morph yielded a lower Dice score in this case, it bett... | ACB | CAB | CBA | ACB | Selection 3 |
**A**:
We fix the beam design at the BS, as stated in Section II-B, while considering different beam design methods for the RIS**B**: The training beams at the RIS are designed as follows: (i) random beams (each element of the beam vectors is constant modulus with random phase), (ii) low phase resolution, e.g., one-bi... | BCA | ABC | CAB | ACB | Selection 2 |
**A**:
So far, we have seen that there is generally a trade-off between ID and OOD performance**B**: In this subsection, we ask whether selective calibration can ensure a synergistic use of OCM and calibration-aware regularization, guaranteeing that CBNN-OCM achieves the best ID and OOD performance levels. To address ... | BAC | BCA | BAC | ACB | Selection 4 |
**A**: The simulation results are depicted in Fig. 5. Notably, RCS values exhibit a substantial impact on the accuracy of angular parameter estimation (as discussed in Section IV-B), which in turn affects the passive 3D drone localization performance.**B**: Hence, we evaluate the following three cases: ζ∈{0.5,1,2}𝜁0.5... | ABC | BCA | CBA | CAB | Selection 3 |
**A**: Symbol-level synchronization and sufficient channel coherence time across all agents are assumed to facilitate AirComp design. However, under high mobility, such conditions may not hold, requiring advanced scheduling and air-interface designs.**B**:
We acknowledge that several assumptions have been made in this... | CAB | ACB | BAC | BAC | Selection 1 |
**A**: [63] proposed a patch-based graph Laplacian regularization for point cloud denoising. Dinesh et al. [13] proposed a feature graph Laplacian regularization for point cloud denoising**B**:
The graph and mesh-based regularization methods have been widely considered to handle unstructured representations beyond reg... | ABC | CBA | ABC | BAC | Selection 4 |
**A**: After experimentation, we adopted a three-layer architecture with a hidden size of 32, balancing accuracy and training efficiency. The LSTM output feeds into a fully connected perceptron to generate a single feature output**B**: The total number of trainable parameters in the LSTM is 22,508. The architecture is ... | CBA | BAC | ABC | BCA | Selection 4 |
**A**: Section III elaborates on the proposed joint DRL-based solution**B**: Section IV presents the numerical findings, while Section V encapsulates the conclusions drawn from this study.**C**:
The rest of the paper is structured as follows: Section II delineates the system model and problem formulation | BCA | ABC | BAC | CAB | Selection 1 |
**A**: Our research focuses on investigating techniques that can be applied to various TTS architectures for multi-speaker multi-accent speech synthesis, rather than being limited to a specific TTS model**B**: Tacotron 2 serves as an illustrative example to demonstrate the effectiveness of our approach.**C**:
Note tha... | BCA | BAC | ACB | ABC | Selection 1 |
**A**: Stratified 10-fold cross-validation is used which combines stratification and cross-validation, providing a robust means to thoroughly assess model performance**B**: Stratification groups data by class labels to maintain class distribution and 10-Fold Cross-Validation divides data into 10 subsets**C**: Iterates ... | ABC | BAC | CBA | CAB | Selection 1 |
**A**: Besides the aforementioned quantitative comparisons among different methods, visual assessments and comparisons are also conducted between MEFN and other state-of-the-art multi-modal tumor segmentation methods. Fig. 4 gives the segmented results from different methods for three different CT sample images of pati... | BAC | CBA | ABC | CBA | Selection 3 |
**A**: Instead of using CLAP [1] for computing the audio and text embedding, our experiments replaced the encoder with a T5 [2] encoder for condition embedding, and an cross-attention module [21] is applied to process the T5 embedding**B**: We name the system as AudioLDM-T5**C**: For the remaining modules, we follow th... | ACB | CAB | ABC | CAB | Selection 3 |
**A**: The acquisition protocols in terms of exposure, exposure time, X-ray tube current, and contrast bolus volume vary across locations**B**: Manufacture acronyms are P: Philips, S: Siemens, T: Toshiba.
**C**: Three manufacturers with in total eleven different models were included in the federated training | BCA | ABC | ACB | ACB | Selection 1 |
**A**: In Section III, we propose the AO algorithm to solve the optimization problem. Next, simulation results and discussions are provided in Section IV. Finally, this paper is concluded in Section V.
**B**: The rest of this paper is organized as follows**C**: Section II introduces the system model and the optimizatio... | ACB | CAB | ABC | BCA | Selection 2 |
**A**: Related to [32], [33] presents a sample-based model for calculating additional manual reserves**B**: However, these approaches yield an NP-hard problem and require approximations to be computed efficiently. Such approximations have been studied in recent literature, e.g, [34, 35, 36, 37]. Still, these approximat... | BCA | CAB | ABC | CBA | Selection 1 |
**A**: We observe that these factors can affect each other, necessitating a focus on specific time slots to capture the underlying physics-based relationships**B**:
The correlation analysis indicates that factors such as electricity market prices, average temperatures across Texas, and ERCOT-wide electricity demand in... | ACB | CBA | BAC | CAB | Selection 3 |
**A**: Moreover, in order to verify the effectiveness according to the amount of adaptation data, we additionally conduct experiments by utilizing 15, 30, and 45 minutes of adaptation data.**B**:
One of the challenges in speaker-adaptive lip reading is that it is not easy to collect sufficient data for the target spea... | CAB | ABC | BCA | BCA | Selection 1 |
**A**: Consequently, the input to the speech decoder includes the audio codes, the watermarks, and the masked features.
**B**: The masked encoder shares the same architecture as the Encodec encoder and is initialized with parameters from Encodec**C**: Specifically, we mask the edited segments of the original waveform w... | CBA | ACB | ABC | ABC | Selection 1 |
**A**: In contrast, Transformer-based models effectively capture global information through self-attention mechanisms and perform remote spatial modeling [10]. However, their quadratic complexity related to image size results in substantial computational costs, especially in pixel-dense prediction tasks such as medical... | BAC | CAB | BCA | ACB | Selection 2 |
**A**: We evaluated the performance of language-oriented TSE in real-world application scenarios using the real evaluation data described in Section III-A3**B**: Each subject was asked to evaluate 41 audio pairs for each model**C**: Each audio pair included the original mixture, a description of the target sound, and t... | CAB | BCA | ACB | ABC | Selection 4 |
**A**: By integrating shape information and leveraging advanced neural network architectures, we provide a comprehensive solution that overcomes the limitations of existing methods, ensuring accurate and reliable motion correction in real-time clinical settings**B**: This advancement represents a significant step forwa... | BAC | CBA | CAB | BCA | Selection 4 |
**A**: It then computes the sampling decisions for all agents, and communicates these decisions to each agent. These decisions are disseminated in batches, allowing multiple agents to simultaneously sample points, parallelizing the optimization process [23], [24].**B**:
We are interested in multi-agent BO, where multi... | CAB | ABC | ACB | BAC | Selection 1 |
**A**: (original questions), Emp**B**: (emphasis setting), Neg. (negative questions setting), and MATCH (the proposed Multi-turn And Thoughtful Chain of Hearings setting).
Underlined text indicates the best performance.**C**: The results are shown for four different settings: Orig | CBA | ABC | BCA | CBA | Selection 3 |
**A**: Upon receiving the encoded Delta-frames, the server decodes them and overlays these Delta-frames with the corresponding RF-frames to reconstruct the original CAV-frames, called Rec-frames. Advanced DL techniques are then applied to the Rec-frames to perform downstream tasks (e.g., object detection, semantic segm... | CBA | BCA | BAC | BCA | Selection 1 |
**A**: This computational overhead resulted in longer total processing times and thus higher energy consumption of 71x and 52x of the raw-signal model, respectively, which could be detrimental in time-critical and energy-sensitive applications**B**: However, these models maintained high classification performances, sug... | CAB | BCA | CAB | BAC | Selection 2 |
**A**:
Approximations and learning for POMDPs under the average cost criterion is significantly more challenging**B**: Several papers [51, 25, 53, 31] have studied the average-cost control problem under the assumption that the state space is finite; they provide reachability type conditions for the belief kernels. Ref... | CBA | BAC | BAC | ACB | Selection 4 |
**A**: As N𝑁Nitalic_N increases from 1 to 3, there is a consistent improvement in objective performance metrics, including PESQ, STOI, and three MOS scores, demonstrating the efficacy of adding TS-Mamba blocks in enhancing speech quality**B**: The experiments in Table IV investigate the impact of varying the number of... | BAC | CBA | CAB | CBA | Selection 1 |
**A**:
Impact of CNN subsampling with LoRA adaptation We compare the performance of various spoken language models trained following the methodology we presented in Section II. Rows 4 and 5 of Table I show the results of trained language paris with and without LoRa adaptation**B**: Comparing rows 5 and 6, where we per... | BAC | ACB | CBA | CAB | Selection 2 |
**A**: First, the current text is input into the Text Encoder to generate current text feature. Then, the face frames, text, and audio from the previous and following sentences are respectively fed into their own M2CI encoders, while interacting with the current text feature to generate fused global-local features. Fin... | BAC | CBA | BAC | CAB | Selection 4 |
**A**: The terms of +SE, +CC and +PAPB represent the application of spectral enhancement, cross-centre loss [9] and PABA loss, respectively. As observed, the baseline achieves 69.6% Rank-1 and 66.8% mAP on the SYSU-MM01 dataset (All-search mode)**B**: When the proposed spectral enhancement strategy is utilized to reduc... | CBA | BCA | ACB | ACB | Selection 2 |
**A**: The blood vessels in the Hepatic appear as tiny spots in cross-section, due to the vessel branches being elongated tubular structures. Therefore, the task of localizing blood vessels in the Hepatic is similar to the segmentation problem of small objects**B**: To address this issue, recent studies have introduced... | BCA | ACB | BCA | CAB | Selection 2 |
**A**: Recently, quantum machine learning (QML) has gained significant attention in the field of wireless communications. The principles of quantum superposition and quantum entanglement offer a fundamental rethinking of traditional approaches, providing new insights to enhance the mainstream DNN-based architecture. Du... | ACB | ABC | CAB | BAC | Selection 2 |
**A**: This is likely due to the directional nature of Max-Dir measurements, which has a smaller number of strong paths, and thus less “shadowing diversity" compared to the omnidirectional case.
**B**: The Max-Dir case experiences slightly larger variance of the shadowing compared to the omni-directional case, Figs**C*... | CAB | ABC | ACB | BCA | Selection 1 |
**A**: 2023). To address this issue, data-driven methods, such as DNN-based direction finding techniques, have surged exponential popularity (Ghourchian, Allegue-Martinez, and Precup 2017; Mo and Morgado 2023)**B**: Nonetheless, the accuracy of such methods is heavily reliant on the availability of massive data sets, w... | ACB | CBA | ABC | BCA | Selection 4 |
**A**: To address this, we propose SECodec, which can automatically determines the appropriate codebook size and integrates structural information into the quantization process.
Extensive experiments demonstrate that SECodec outperforms EnCodec in speech reconstruction**B**: Furthermore, we developed a Structural Entro... | BCA | ACB | CBA | ACB | Selection 1 |
**A**: This may be because gestures usually contain clear and consistent patterns, such as regular sounds when tapping and snapping sounds when patting, so the model can capture sounds produced by specific movements and rhythms to identify touch gestures effectively**B**: However, due to the variety of ways in which di... | BCA | CBA | CBA | ABC | Selection 1 |
**A**: The first step towards modifying the LLM to understand speech is to tokenize the speech**B**: Since the LLM first applies a tokenizer such as a sentence-piece [18] or word-piece [19] tokenizer to break text into a fixed vocabulary and takes discrete indices in the vocabulary as input, our key idea is to simply r... | BCA | CAB | CBA | ACB | Selection 4 |
**A**:
In conclusion, this framework enables LLM to be coupled to physical systems as a dynamic digital twin by leveraging abstraction forms**B**: Our experimental result demonstrates the potential application value of LLM as a digital twin**C**: Although some limitations are caused by LLM features, the development of... | BCA | CAB | ABC | BCA | Selection 3 |
**A**: Prov-GigaPath utilized the AutoGluon model derived from CONCH to evaluate its transferability.
**B**: In contrast, for UNI, CONCH, and TITAN, their respective tile encoders were used to extract tile representations, and AutoGluon was trained from scratch to derive tile-level ambiguity scores**C**: For Inception-... | BCA | BAC | CBA | BAC | Selection 3 |
**A**: (2) SPRSound [3]: It annotates at record and event levels with seven class labels**B**: We use event level in our experiment. (3) HF [4]: It shares similarities with SPRSound but introduces additional labels for inhale and exhale phases alongside four abnormal respiratory sound classes. However, it lacks annotat... | ACB | BCA | BAC | CAB | Selection 2 |
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