Custom YOLO Object Detection Model for COVID-19 Diagnosis by Noor Najah Ali, Aseel Hameed, Asanka G. Perera, Ali Al_Naji

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Advanced Diabetic Retinopathy Detection with the R–CNN: A Unified Visual Health Solution by Sravya Valluri Sri, Srinivasu Parvathaneni Naga, Shafi Jana, Hołubowski Waldemar, Zielonka Adam

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Solar Radio Burst Detection Based on Deformable DETR by Mingming Wang, Guowu Yuan, Hao Zhou, Chengming Tan, Hao Wu

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Comparisons of different deep learning-based methods on fault diagnosis for geared system by Bing Han, Xiaohui Yang, Yafeng Ren, Wanggui Lan

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Accurately Identifying Different Ripening Stages of Strawberry Fruits in Complex Agricultural Scenarios by Xuefeng Ren, Yang Gan, Huan Liu, Yongming Chen, Ping Lin

“…Second, a receptive field coordinate attention convolutional mechanism is incorporated into the backbone network to enhance parameter sharing of convolutional kernels. …”
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Assessment of Bone Aging—A Comparison of Different Methods for Evaluating Bone Tissue by Paweł Kamiński, Aleksander Gali, Rafał Obuchowicz, Michał Strzelecki, Adam Piórkowski, Marcin Kociołek, Elżbieta Pociask, Joanna Kwiecień, Karolina Nurzyńska

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Pattern transition recognition based on transfer learning for exoskeleton across different terrains by Yifan Gao, Jianbin Zheng, Yang Gao, Ziyao Chen, Jing Tang, Liping Huang

“…In the study, a novel transfer learning method based on temporal convolutional network spatial attention (TCN-SA) is applied for pattern transition recognition under triple physical loads on different terrains. …”
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Evaluation of Different Generative Models to Support the Validation of Advanced Driver Assistance Systems by Manasa Mariam Mammen, Zafer Kayatas, Dieter Bestle

“…To overcome these limitations, the paper explores AI-based methods for scenario generation, with a focus on the cut-in maneuver. Four different approaches are trained and compared: Variational Autoencoder enhanced with a convolutional neural network (VAE), a basic Generative Adversarial Network (GAN), Wasserstein GAN (WGAN), and Time-Series GAN (TimeGAN). …”
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Online Pre-Diagnosis of Multiple Faults in Proton Exchange Membrane Fuel Cells by Convolutional Neural Network Based Bi-Directional Long Short-Term Memory Parallel Model with Atten... by Junyi Chen, Huijun Ran, Ziyang Chen, Trevor Hocksun Kwan, Qinghe Yao

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A 3D Dual Encoder Mirror Difference ResU-Net for Multimodal Brain Tumor Segmentation by Qiwei Xing, Zhihua Li, Yongxia Jing, Xiaolin Chen

“…Additionally, residual blocks are employed to substitute the original convolutional blocks in the encoder section of the U-Net structure. …”
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Fully-Gated Denoising Auto-Encoder for Artifact Reduction in ECG Signals by Ahmed Shaheen, Liang Ye, Chrishni Karunaratne, Tapio Seppänen

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Joint classification and regression with deep multi task learning model using conventional based patch extraction for brain disease diagnosis by Padmapriya K., Ezhumalai Periyathambi

“…The proposed model learns many tasks concurrently, such as categorizing different brain diseases or anomalies, by extracting features from image patches using convolutional neural networks (CNNs). …”
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A Parallel Image Denoising Network Based on Nonparametric Attention and Multiscale Feature Fusion by Jing Mao, Lianming Sun, Jie Chen, Shunyuan Yu

“…The lower branch network used multiple dilation convolution residual blocks with different dilation rates to increase the receptive field and extend more contextual information to obtain the global features of the noise in the image. …”
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MT-SCnet: multi-scale token divided and spatial-channel fusion transformer network for microscopic hyperspectral image segmentation by Xueying Cao, Hongmin Gao, Haoyan Zhang, Shuyu Fei, Peipei Xu, Peipei Xu, Zhijian Wang

“…It divides token at different scale based on mirror padding and promotes information interaction and fusion between different tokens to obtain more representative features for subsequent global feature extraction. …”
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A Low-Complexity Transformer-CNN Hybrid Model Combining Dynamic Attention for Remote Sensing Image Compression by L. L. Zhang，X. J. Wang，J. H. Liu, Q. Z. Fang

“…However, conventional CNN is complex to adaptively capture important information from different image regions. In addition, previous transformer-based compression methods have introduced high computational complexity to the models. …”
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A deep classification model to assess environment following hazards using remote sensing images by Madhusmita Sahu, Rasmita Dash

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StrawberryNet: Fast and Precise Recognition of Strawberry Disease Based on Channel and Spatial Information Reconstruction by Xiang Li, Lin Jiao, Kang Liu, Qihuang Liu, Ziyan Wang

“…First, to decrease the number of parameters, instead of standard convolution, a partial convolution is selected to construct the backbone for extracting the features of strawberry disease, which can significantly improve efficiency. …”
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DPN-GAN: Inducing Periodic Activations in Generative Adversarial Networks for High-Fidelity Audio Synthesis by Zeeshan Ahmad, Shudi Bao, Meng Chen

“…For evaluation, we use five different datasets, covering both speech synthesis and music generation tasks, to demonstrate the efficiency of the DPN-GAN. …”
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A Feature-Driven Inception Dilated Network for Infrared Image Super-Resolution Reconstruction by Jiaxin Huang, Huicong Wang, Yuhan Li, Shijian Liu

“…Furthermore, deformable convolution is utilized to fuse features extracted from different branches, enabling adaptation to targets of various shapes. …”
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ERNIE-TextCNN: research on classification methods of Chinese news headlines in different situations by Yumin Yan

“…To rapidly extract deep features from news headlines and enhance the classification performance of extremely short Chinese news headlines, we delve into the inherent characteristics of news headline data, focusing on multi-domain news classification problems and studying datasets of different scales. For the classification of large-scale extremely short Chinese news headline datasets, which are affected by feature sparsity and insufficient representation, we construct an improved convolutional classification model, ERNIE-AAFF-SECNN, based on an adaptive feature fusion mechanism. …”
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