DeSPPNet: A Multiscale Deep Learning Model for Cardiac Segmentation by Elizar Elizar, Rusdha Muharar, Mohd Asyraf Zulkifley

“…The SPP layer is designed to pool features from densely convolutional layers at different scales or sizes, which will be combined to maintain a set of spatial information. …”
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Cross-Scenario Subdomain Adaptive Displacement Anomaly Detection in Dams by Yu Wang, Guohua Liu

“…To overcome the challenges of limited data, domain distribution differences, and the need for retraining in unsupervised learning methods for cross-scenario anomaly detection in dams, this study introduces a novel approach; the Temporal Displacement Subdomain Adaptation Network (TDSAN) combines temporal convolutional networks with subdomain adaption. …”
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An integrated approach for advanced vehicle classification. by Rui Liu, Shiyuan Wen, Yufei Xing

“…The DWAN model can identify and accurately classify subtle features and differences in automotive images, resulting in better classification results for the automotive fine-grained category. …”
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CNN Performance Improvement for Classifying Stunted Facial Images Using Early Stopping Approach by Yunidar Yunidar, Y Yusni, N Nasaruddin, Fitri Arnia

“…Children affected by stunting usually show different physical and cognitive characteristics compared to their peers. …”
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Integrating Viewing Direction and Image Features for Robust Multi-View Multi-Object 3D Pedestrian Tracking by R. Ali, M. Mehltretter, C. Heipke

“…However, many of these developments do not address the critical challenge of generalization across different camera constellations, i.e., having camera constellations that differ between training and testing, limiting their effectiveness in real-world applications. …”
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Multi-Scale Long- and Short-Range Structure Aggregation Learning for Low-Illumination Remote Sensing Imagery Enhancement by Yu Cao, Yuyuan Tian, Xiuqin Su, Meilin Xie, Wei Hao, Haitao Wang, Fan Wang

“…Profiting from the surprising non-linear expressive capacity, deep convolutional neural networks have inspired lots of progress in low illumination (LI) remote sensing image enhancement. …”
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Evaluation of YOLO Efficiency in Automatic Orange Detection in Multi-Exposure Images by M. R. Oviedo Espinosa, L. R. Porto, V. S. W. Orlando, A. M. G. Tommaselli, A. P. Dal Poz, N. N. Imai

“…In this sense, this paper focus on the detection of oranges in multispectral images, with different spectral bands and exposures, using a convolutional neural network (CNN) known as YOU ONLY LOOK ONCE (YOLO). …”
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Real-Time Waste Detection and Classification Using YOLOv12-Based Deep Learning Model by Mosharof Hossain Dipo, Fahmid Al Farid, Md. Sifti Al Mahmud, Muntasir Momtaz, Shakila Rahman, Jia Uddin, Hezerul Abdul Karim

“…Images of waste were captured in many different settings and analyzed with a YOLOv12-based model. …”
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A Hybrid Framework for Photovoltaic Power Forecasting Using Shifted Windows Transformer-Based Spatiotemporal Feature Extraction by Ping Tang, Ying Su, Weisheng Zhao, Qian Wang, Lianglin Zou, Jifeng Song

“…The experimental results indicate that the proposed framework demonstrates competitive predictive performance and generalization capability across different time horizons and weather conditions compared with benchmark frameworks.…”
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Forecasting Surface Velocity Fields Associated With Laboratory Seismic Cycles Using Deep Learning by G. Mastella, F. Corbi, J. Bedford, F. Funiciello, M. Rosenau

“…The onset, magnitude, and propagation of analog earthquakes can thus be predicted at different prediction horizons. From all architectures tested in this study, convolutional recurrent neural networks (CNN‐LSTM and CONVLSTM) provide the best predictions although their performances depend on experiment characteristics and hyperparameters tuning. …”
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Intelligent Sports Weights by Olga dos Santos Duarte, Gustavo Jacinto, Mário Véstias, Rui Policarpo Duarte

“…To counter this, this work proposes a different approach to automatic weightlifting supervision off-the-person. …”
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LayerFold: A Python library to reduce the depth of neural networks by Giommaria Pilo, Nour Hezbri, André Pereira e Ferreira, Victor Quétu, Enzo Tartaglione

“…Large-scale models are the backbone of Computer Vision and Natural Language Processing, and their generalizability allows for transfer learning and deployment in different scenarios. However, their large size means that reducing their computational and memory demands remains a challenge. …”
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Application of Traffic Cone Target Detection Algorithm Based on Improved YOLOv5 by Mingwu Wang, Dan Qu, Zedong Wu, Ao Li, Nan Wang, Xinming Zhang

“…The experimental results show that the network could maintain recognition accuracy and speed values of around 89% and 9 fps under different working conditions such as varying distances, lighting conditions, and occlusions, meeting the technical requirements for deploying and retrieving cones at a speed of 30 cones per minute when the operating vehicle’s speed was 20 km/h. …”
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Software Defect Prediction Based On Deep Learning Algorithms : A Systematic Literature Review by Akhlas Hasan, Shayma Mohi-Aldeen

“…Deep learning techniques are widely used in SDP, which can produce accurate and exceptional results in different fields.The study aims to systematically review models, techniques, datasets, and performance evaluation metrics to gain a complete understanding of current methodologies related to SDP, and the use of DL in software defect prediction research between 2019 and 2024. …”
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Expanding the Reach of Structured EHR Data with Clinical Notes by Seda Bilaloglu, Vincent J Major, Himanshu Grover, Isabel Metzger, Yindalon Aphinyanaphongs

“…Patients of both groups do die in the following months suggesting the two approaches identify different patient phenotypes which supplement one another. …”
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SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs. by Jamil Ahmad, Muhammad Sajjad, Irfan Mehmood, Sung Wook Baik

“…Neuronal activation features termed as neural codes from different CNN layers are comprehensively studied to identify most appropriate features for representing radiographs. …”
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Multi-task deep learning framework for enhancing Mayo endoscopic score classification in ulcerative colitis by Jaehyuk Lee, Eunchan Kim

“…Future studies should explore integrating multiple convolutional neural network-based models to further boost classification accuracy.…”
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Bridging neuroscience and AI: a survey on large language models for neurological signal interpretation by Sreejith Chandrasekharan, Jisu Elsa Jacob

“…Traditional deep neural networks, such as convolutional networks, sequence-to-sequence networks, and hybrids of such neural networks were proven to be effective for a wide range of neurological disease classifications. …”
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Automatic serving method of volleyball training robot based on improved YOLOv5 and improved Hough transform by Tao Sun, Xiaolong He, Jiajun Zhang

“…Abstract Volleyball training robots play an important role in modern sports training, and their automatic serving technology can simulate serving modes in different scenarios, providing athletes with diverse training programs. …”
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Wind energy system fault classification using deep CNN and improved PSO‐tuned extreme gradient boosting by Chun‐Yao Lee, Edu Daryl C. Maceren

“…The effectiveness of the proposed method is demonstrated through validation conducted on a different imbalanced dataset showing superior performance metrics in terms of accuracy. …”
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