A Hybrid Deep Learning Framework for Deepfake Detection Using Temporal and Spatial Features by Fazeel Zafar, Talha Ahmed Khan, Salas Akbar, Muhammad Talha Ubaid, Sameena Javaid, Kushsairy Abdul Kadir

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Computer-aided diagnosis of Haematologic disorders detection based on spatial feature learning networks using blood cell images by Jamal Alsamri, Hamed Alqahtani, Ali M. Al-Sharafi, Abdulbasit A. Darem, Khalid Nazim, Abdul Sattar, Menwa Alshammeri, Ahmad A. Alzahrani, Marwa Obayya

“…This study presents a novel Computer-Aided Diagnosis of Haematologic Disorders Detection Based on Spatial Feature Learning Networks with Hybrid Model (CADHDD-SFLNHM) approach using Blood Cell Images. …”
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An Anomaly Node Detection Method for Wireless Sensor Networks Based on Deep Metric Learning with Fusion of Spatial–Temporal Features by Ziheng Wang, Miao Ye, Jin Cheng, Cheng Zhu, Yong Wang

“…Additionally, they struggle with small sample scenarios because they do not effectively map features to classes. To address these challenges, this paper presents an anomaly detection approach that integrates deep learning with metric learning. …”
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Classification Model of Clock Drawing Test Based on Contrastive Learning Using Multi-Channel Features With Channel-Spatial Attention by Changsu Kang, Bohyun Wang, J. S. Lim

“…The features obtained from the multiple channels of the MCC-net were used to compute contrastive loss and learn representations of the data. …”
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Learning spatial‐frequency interaction for generalizable deepfake detection by Tianbo Zhai, Kaiyin Lu, Jiajun Li, Yukai Wang, Wenjie Zhang, Peipeng Yu, Zhihua Xia

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Mesh representation matters: investigating the influence of different mesh features on perceptual and spatial fidelity of deep 3D morphable models by Robert KOSK, Richard SOUTHERN, Lihua YOU, Shaojun BIAN, Willem KOKKE, Greg MAGUIRE

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Flood Classification and Improved Loss Function by Combining Deep Learning Models to Improve Water Level Prediction in a Small Mountain Watershed by Rukai Wang, Ximin Yuan, Fuchang Tian, Minghui Liu, Xiujie Wang, Xiaobin Li, Minrui Wu

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Multimodal scene recognition using semantic segmentation and deep learning integration by Aysha Naseer, Mohammed Alnusayri, Haifa F. Alhasson, Mohammed Alatiyyah, Dina Abdulaziz AlHammadi, Ahmad Jalal, Jeongmin Park

“…Semantic modeling and recognition of indoor scenes present a significant challenge due to the complex composition of generic scenes, which contain a variety of features including themes and objects, makes semantic modeling and indoor scene recognition difficult. …”
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LETSmix: a spatially informed and learning-based domain adaptation method for cell-type deconvolution in spatial transcriptomics by Yangen Zhan, Yongbing Zhang, Zheqi Hu, Yifeng Wang, Zirui Zhu, Sijing Du, Xiangming Yan, Xiu Li

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Temporal-Spatial Feature Extraction in IoT-Based SCADA System Security: Hybrid CNN-LSTM and Attention-Based Architectures for Malware Classification and Attack Detection by Onur Polat, Ali Ayid Ahmad, Saadin Oyucu, Enes Algul, Ferdi Dogan, Ahmet Aksoz

“…The developed model identifies complex attacks in the network by taking advantage of the strengths of CNNs that reveal spatial features and LSTMs that detect temporal dependency. …”
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Spatial-Temporal Semantic Feature Interaction Network for Semantic Change Detection in Remote Sensing Images by Yuhang Zhang, Wuxia Zhang, Songtao Ding, Siyuan Wu, Xiaoqiang Lu

“…Moreover, Mixed Spatial Reasoning Convolution block (MixSrc) is presented to enrich the spatial information by extracting the multiscale features, thus improving the model's capability to interpret complex scenes. …”
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GeoFAN: Point Pattern Recognition in Spatial Vector Data by Zhuoyi Yang, Zeyi Li, Haitao Zhang, Wei Zhang, Yanwei Wang, Yihang Huang

“…We also present an implementation of the scheme based on the graph method, termed GeoFAN, to extract and classify point patterns simultaneously in spatial vector data. …”
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Improving Face Presentation Attack Detection Through Deformable Convolution and Transfer Learning by Shakeel Muhammad Ibrahim, Muhammad Sohail Ibrahim, Shujaat Khan, Young-Woong Ko, Jeong-Gun Lee

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Plant Disease Prognosis Using Spatial-Exploitation-Based Deep-Learning Models by Jayavani Vankara, Sekharamahanti S. Nandini, Murali Krishna Muddada, N. Satya Chitra Kuppili, K Sowjanya Naidu

“…Our model’s results are compared to those of other spatial exploitation models. The results show that the proposed method is superior to the standard deep-learning classifier. …”
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High-Order and Interactive Perceptual Feature Learning for Medical Image Retargeting by Mingjuan Ma, Yuehong Zhang

“…This process enhances the display of CT images, which can be particularly beneficial for applications like medical education, enabling optimal presentation of CT images to students. This study explores an innovative approach to CT image retargeting by effectively fusing gaze shift path (GSP) features using a hypergraph framework to address the complex spatial layout of CT images. …”
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A Deep Learning Approach for Spatiotemporal Feature Classification of Infrasound Signals by Xiaofeng Tan, Xihai Li, Hongru Li, Xiaoniu Zeng, Shengjie Luo, Tianyou Liu

“…Building upon this representation, we develop an advanced hybrid deep learning architecture that integrates ConvLSTM networks to simultaneously extract and correlate spatial and spectral features. …”
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Corrections to “Gradual Variation-Based Dual-Stream Deep Learning for Spatial Feature Enhancement With Dimensionality Reduction in Early Alzheimer’s Disease Detection... by Najmul Hassan, Abu Saleh Musa Miah, Taro Suzuki, Jungpil Shin

“…Presents corrections to the paper, (Corrections to “Gradual Variation-Based Dual-Stream Deep Learning for Spatial Feature Enhancement With Dimensionality Reduction in Early Alzheimer’s Disease Detection”).…”
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MuCST: restoring and integrating heterogeneous morphology images and spatial transcriptomics data with contrastive learning by Yu Wang, Zaiyi Liu, Xiaoke Ma

“…Integrative analysis of multi-modal SRT data holds immense potential for understanding biological mechanisms. Here, we present a flexible multi-modal contrastive learning for the integration of SRT data (MuCST), which joins denoising, heterogeneity elimination, and compatible feature learning. …”
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HiSTENet: History-Integrated Spatial–Temporal Information Extraction Network for Time Series Remote Sensing Image Change Detection by Lu Zhao, Ling Wan, Lei Ma, Yiming Zhang

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Learning Spectral–Spatial-Former Deep Prior for Hyperspectral Image Superresolution by Zeinab Dehghan, Jingxiang Yang, Abdolraheem Khader, Jian Fang, Liang Xiao

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