Post-disaster flooded region segmentation using DeepLabv3+ and unmanned aerial system imagery by Akila Agnes Sundaresan, Appadurai Arun Solomon

“…ResNet-50 proves to be the most effective backbone, achieving the optimal balance between segmentation accuracy and computational efficiency. …”
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Enhanced Localisation and Handwritten Digit Recognition Using ConvCARU by Sio-Kei Im, Ka-Hou Chan

“…This ensures the enhanced extraction and preservation of spatial and temporal features through convolution-based gating and adaptive fusion mechanisms. …”
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A Power-Efficient 0.5668 TOPS/W Digital Logic Accelerator Implemented Using 40-nm CMOS Process for Underwater Object Recognition Usage by Chua-Chin Wang, Shih-Heng Luo, Hsin-Che Wu, Ralph Gerard B. Sangalang, Chewn-Pu Jou, Harry Hsia, Lan-Chou Cho

“…However, most prior AI hardware works either suffered from high on-silicon area cost or low usage thereof. …”
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STARNet: A Deep‐Learning Algorithm for Surface Shortwave Radiation Retrieval From Fengyun‐4A by Mengmeng Song, Dazhi Yang, Hongrong Shi, Yun Chen, Bai Liu, Yanbo Shen, Zijing Ding, Xiang'ao Xia

“…True out‐of‐sample verification demonstrates that STARNet can outperform physical and conventional data‐driven retrieval algorithms. Most importantly, STARNet is exceedingly general and thus applicable to many other retrieval tasks, such as those for aerosols or clouds.…”
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A Robust Hybrid CNN+ViT Framework for Breast Cancer Classification Using Mammogram Images by Vasudha Rani Patheda, Gunda Laxmisai, B. V. Gokulnath, S. P. Siddique Ibrahim, S. Selva Kumar

“…Breast cancer is the most frequent type of cancer largely experienced by women currently, although it could happen to men also. …”
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Multitemporal Difference and Dynamic Optimization Framework for Multiscale Motion Satellite Video Super-Resolution by Qian Zhao, Youming Guo, Lei Min, Changhui Rao

“…Motion alignment is a critical task in satellite video super-resolution. Most existing methods rely on optical flow or deformable convolution for motion alignment. …”
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Few-shot biomedical NER empowered by LLMs-assisted data augmentation and multi-scale feature extraction by Di Zhao, Wenxuan Mu, Xiangxing Jia, Shuang Liu, Yonghe Chu, Jiana Meng, Hongfei Lin

“…Simultaneously, we employ dynamic convolution to capture multi-scale semantic information in sentences and enhance feature representation based on PubMedBERT. …”
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A Reaction-Based Approach to Colorimetric Detection of Organic Analytes in Water Using a Chlorine-Containing Carbocyanine Dye and Hypochlorite by Anna V. Shik, Evgenii V. Skorobogatov, Ramil M. Akhmetov, Irina A. Doroshenko, Tatyana A. Podrugina, Gleb K. Sugakov, Mikhail K. Beklemishev

“…Water quality control employs techniques mostly targeting individual analytes; group detection is also practiced, but the choice of group methods is limited, which supports interest in developing such methods. …”
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Distinguishing Difficulty Imbalances in Strawberry Ripeness Instances in a Complex Farmland Environment by Yang Gan, Xuefeng Ren, Huan Liu, Yongming Chen, Ping Lin

“…Additionally, our model is better in detection performance than most models with fewer parameters and lower FLOPs. …”
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Bird Species Detection Net: Bird Species Detection Based on the Extraction of Local Details and Global Information Using a Dual-Feature Mixer by Chaoyang Li, Zhipeng He, Kai Lu, Chaoyang Fang

“…However, this task remains challenging due to local structural similarities and class imbalances among bird species. Currently, most deep learning algorithms focus on designing local feature extraction modules while ignoring the importance of global information. …”
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BiAttentionNet: a dual-branch automatic driving image segmentation network integrating spatial and channel attention mechanisms by Ruijun Liu, Yijun Zhang, Jieying Chen, Zhigang Wu, Yaohui Zhu, Jun Liu, Min Chen

“…Abstract Real-time semantic segmentation is one of the most researched areas in the field of computer vision, and research on dual-branch networks has gradually become a popular direction in network architecture research. …”
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Multimodal Deep Learning Model for Cylindrical Grasp Prediction Using Surface Electromyography and Contextual Data During Reaching by Raquel Lázaro, Margarita Vergara, Antonio Morales, Ramón A. Mollineda

“…In this context, the identification of patterns and prediction of hand grasp types is crucial, with cylindrical grasp being one of the most common and functional. Traditional approaches to grasp prediction often rely on unimodal data sources, limiting their ability to capture the complexity of real-world scenarios. …”
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Solar Wind Speed Prediction via Graph Attention Network by Yanru Sun, Zongxia Xie, Haocheng Wang, Xin Huang, Qinghua Hu

“…Second, our approach employs the dilated causal convolution to extend the receptive field and prolong the prediction time. …”
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Diagnosis and Detection of Alzheimer’s Disease Using Learning Algorithm by Gargi Pant Shukla, Santosh Kumar, Saroj Kumar Pandey, Rohit Agarwal, Neeraj Varshney, Ankit Kumar

“…The studies of these diseases are carried out by Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), and Computed Tomography (CT) scans which require expertise to understand the modality. The disease is the most prevalent in the elderly and can be fatal in its later stages. …”
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Injecting structure-aware insights for the learning of RNA sequence representations to identify m6A modification sites by Yue Yu, Shuang Xiang, Minghao Wu

“…N6-methyladenosine (m6A) represents one of the most prevalent methylation modifications in eukaryotes and it is crucial to accurately identify its modification sites on RNA sequences. …”
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AGCN-T: A Traffic Flow Prediction Model for Spatial-Temporal Network Dynamics by Jian Feng, Lang Yu, Rui Ma

“…Aiming at the lack of the ability to model complex and dynamic spatial-temporal dependencies in current research, this paper proposes a traffic flow prediction model Attention based Graph Convolution Network (GCN) and Transformer (AGCN-T) to model spatial-temporal network dynamics of traffic flow, which can extract dynamic spatial dependence and long-distance temporal dependence to improve the accuracy of multistep traffic prediction. …”
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BG-YOLO: A Bidirectional-Guided Method for Underwater Object Detection by Ruicheng Cao, Ruiteng Zhang, Xinyue Yan, Jian Zhang

“…A feature-guided module connects the shallow convolution layers of the two branches. When training the image enhancement branch, the object detection subnet in the enhancement branch guides the image enhancement subnet to be optimized towards the direction that is most conducive to the detection task. …”
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Evaluation of Dose Calculation Algorithms Accuracy for ISOgray Treatment Planning System in Motorized Wedged Treatment Fields by Sajjad Raghavi, Hamid-Reza Sadoughi, Mohammad Ehsan Ravari, Marziyeh Behmadi

“…Background: Different dose calculation methods vary in accuracy and speed. While most methods sacrifice precision for efficiency Monte Carlo (MC) simulation offers high accuracy but slower calculation. …”
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MAIN TRENDS OF INVESTMENT AND INNOVATIVE ACTIVITY OF BUSINESS ENTITIES IN THE CONDITIONS OF EUROPEAN INTEGRATION by Olena Iastremska, Hanna Strokovych

“…The following results are obtained: to increase the objectivity and reliability of the analysis, the corresponding integral indicators characterizing each level are combined into a generalized integral index of investment and innovation activity of economic entities, calculated by the method of additive convolution, taking into account the coefficients of significance of each level. …”
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Recognition Method of Corn and Rice Crop Growth State Based on Computer Image Processing Technology by Li Tian, Chun Wang, Hailiang Li, Haitian Sun

“…The agriculture field is one of the most important fields where computational techniques play an imperative role for decision-making whether it is the automation of watering of plants, controlling of humidity levels, and detection of plant diseases and growth of plants. …”
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