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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Enhancing sound-based classification of birds and anurans with spectrogram representations and acoustic indices in neural network architectures by Fábio Felix Dias, Moacir Antonelli Ponti, Rosane Minghim

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FFLKCDNet: First Fusion Large-Kernel Change Detection Network for High-Resolution Remote Sensing Images by Bochao Chen, Yapeng Wang, Xu Yang, Xiaochen Yuan, Sio Kei Im

“…FFLKCDNet features a Bi-temporal Feature Fusion Module (BFFM) to fuse remote sensing features from different temporal scales, and an improved ResNet network (RAResNet) that combines large-kernel convolution and multi-attention mechanisms to enhance feature extraction. …”
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Hyperparameter Optimization for Problem-Based Custom CNN Architectures Using a Smart Grid Search Method by H. Aktas

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Forensic of video object removal tamper based on 3D dual-stream network by Lizhi XIONG, Mengqi CAO, Zhangjie FU

“…In order to solve the problems of inaccurate temporal detection and location of the object removal tampered video， a video tamper forensics method based on 3D dual-stream network was proposed.Firstly， the spatial rich model （SRM） layer was used to extract the high-frequency information from video frames.Secondly， the improved 3D convolution （C3D） network was used as the feature extractor of the dual-stream network to extract the high-frequency information and low-frequency information from the high-frequency frame and the original video frame respectively.Finally， through compact bilinear pooling （CBP） layer， two sets of different feature vectors were fused into one set of feature vectors for classification prediction.The experimental results demonstrate that the classification accuracy of the proposed method in all video frames has an advantage in SYSU-OBJFORG dataset， which makes the temporal detection and location of object removal tampered video more accurate.…”
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Quadrature Solution for Fractional Benjamin–Bona–Mahony–Burger Equations by Waleed Mohammed Abdelfattah, Ola Ragb, Mokhtar Mohamed, Mohamed Salah, Abdelfattah Mustafa

“…The novelty of these methods is based on the generalized Caputo sense, classical differential quadrature method, and discrete singular convolution methods based on two different kernels. …”
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DTCNet: finger flexion decoding with three-dimensional ECoG data by Fufeng Wang, Zihe Luo, Wei Lv, XiaoLin Zhu

“…Specifically, current models tend to confuse the movement information of different fingers and fail to fully exploit the dependencies within time series when predicting long sequences, resulting in limited decoding performance. …”
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LSEVGG: An attention mechanism and lightweight-improved VGG network for remote sensing landscape image classification by Yao Lu

“…In this paper, we propose LSEVGG, a novel and efficient CNN architecture that enhances the classic VGG structure through the integration of lightweight convolution techniques and channel attention mechanisms. …”
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Deep LBLS: Accelerated Sky Region Segmentation Using Hybrid Deep CNNs and Lattice Boltzmann Level-Set Model by Fatema A. Albalooshi, M. R. Qader, Yasser Ismail, Wael Elmedany, Hesham Al-Ammal, Muttukrishnan Rajarajan, Vijayan K. Asari

“…The performance of the proposed method is evaluated on the CamVid dataset, which contains images with a wide range of object variations due to factors such as illumination changes, shadow presence, occlusion, scale differences, and cluttered backgrounds. Experiments conducted on this dataset yield promising results in terms of computation time and the robustness of segmentation when compared to state-of-the-art methods. …”
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An innovative methodology for segmenting vessel like structures using artificial intelligence and image processing by Reynaldo Villarreal, Sindy Chamorro-Solano, Steffen Cantillo, Roberto Pestana-Nobles, Sair Arquez, Yolanda Vega-Sampayo, Leonardo Pacheco-Londoño, Jheifer Paez, Nataly Galan-Freyle, Cristian Ayala, Paola Amar

“…The method was applied on different datasets containing images of eye fundus, citrus leaves, printed circuit boards to test how well it could segment the capillary structures. …”
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AsGCL: Attentive and Simple Graph Contrastive Learning for Recommendation by Jie Li, Changchun Yang

“…However, most existing models fail to distinguish the importance of different nodes, which limits their performance. To address this issue, we propose the asGCL model. …”
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A Small-Sample Target Detection Method for Transmission Line Hill Fires Based on Meta-Learning YOLOv11 by Yaoran Huo, Yang Zhang, Jian Xu, Xu Dai, Luocheng Shen, Conghong Liu, Xia Fang

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Detection of Epilepsy Disorder Using Spectrogram Images Generated From Brain EEG Signals by Venkatesh Bhandage, Tejeswar Pokuri, Devansh Desai, Andrew Jeyabose

“…We examined the use of three different pretrained CNN architectures, namely, EfficientNetB0, MobileNetV2, and ResNet18. …”
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YOLOv8-OCHD: A Lightweight Wood Surface Defect Detection Method Based on Improved YOLOv8 by Zuxing Chen, Junjie Feng, Xueyan Zhu, Bin Wang

“…Experimental results show that compared to the YOLOv8n baseline model, the proposed method improves detection accuracy for eight defect types in different tree species, with the mean average precision (mAP) increased by 5.9%. …”
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DFANet: A Deep Feature Attention Network for Building Change Detection in Remote Sensing Imagery by Peigeng Lu, Haiyong Ding, Xiang Tian

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Gesture-controlled reconfigurable metasurface system based on surface electromyography for real-time electromagnetic wave manipulation by Chen Junzai, Li Weiran, Gong Kailuo, Lu Xiaojie, Tong Mei Song, Wang Xiaoyi, Yang Guo-Min

“…Experimental results demonstrate that the proposed system achieves high-precision electromagnetic wave manipulation, in response to different gestures. This system has significant potential applications in intelligent device control, virtual reality systems, and wireless communication technology, and is expected to contribute to the advancement and innovation of HMI technology by integration of more advanced metasurfaces and sEMG processing technologies.…”
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Spatial–Spectral Interaction Super-Resolution CNN–Mamba Network for Fusion of Satellite Hyperspectral and Multispectral Image by Guangwei Zhao, Haitao Wu, Dexiang Luo, Xu Ou, Yu Zhang

“…To solve the above problems, we designed a spatial–spectral interaction super-resolution convolutional neural network (CNN)–Mamba fusion network for satellite HSI and MSI, which uses mutual guidance to improve the spatial and spectral resolution of different data, and obtains the final fused image through feature fusion. …”
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TFTformer: A novel transformer based model for short-term load forecasting by Ahmad Ahmad, Xun Xiao, Huadong Mo, Daoyi Dong

“…Additionally, a Temporal Convolutional Network is integrated within the Transformer’s encoder, employing causal convolutions and dilation to adapt to the sequential nature of data with an expanded receptive field. …”
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Research on Fine-Grained Visual Classification Method Based on Dual-Attention Feature Complementation by Min Huang, Ke Li, Xiaoyan Yu, Chen Yang

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Identifying Bias in Deep Neural Networks Using Image Transforms by Sai Teja Erukude, Akhil Joshi, Lior Shamir

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