Semantic Fusion Algorithm of 2D LiDAR and Camera Based on Contour and Inverse Projection by Xingyu Yuan, Yu Liu, Tifan Xiong, Wei Zeng, Chao Wang

“…The method has two remarkable features: (1) Combined with the ellipse extraction algorithm of the arc support line segment, a LiDAR and camera calibration algorithm based on various regular shapes of an environmental target is proposed, which improves the adaptability of the calibration algorithm to the environment. (2) This paper proposes a semantic segmentation algorithm based on the inverse projection of target contours. …”
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Refining Water Body Extraction by Remote Sensing With Deep Learning Models: Exploring Different Band Combinations by Ziheng Feng, Fei Zhang, Xu Ma, Chi Yung Jim, Di Wu, Dong Liu, Saheed Adeyinka Oke, Weiwei Wang, Lifei Wei, Songlin Nie, Zhihui Li, Haowei Xu

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L'individuazione dei primitivi della Teoria degli Elementi: la questione dell'economia by Laura Bafile

“…The paper discusses the question of “overgeneration”, that in the literature concerning segmental phonology and Element Theory in particular has been often proposed as a major concern affecting the definition of elemental inventories. …”

Grammar or Crammer? The Role of Morphology in Distinguishing Orthographically Similar but Semantically Unrelated Words by Gokhan Ercan, Olcay Taner Yildiz

“…However, morphological segmentation overcomes this issue, boosting accuracy to 68% (English) and 71% (Turkish) without compromising performance on standard benchmarks (RareWords, MTurk771, MEN, AnlamVer). …”
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Multiple Scaling Based EfficientNet Modelling for Liver Tumor Classification on CT Images by Bilga Jacob, R. S. Vinod Kumar, S. S. Kumar

“…Recent, deep Convolutional Neural Network (CNN) research has produced amazing improvements in image segmentation and classification. The same issue of diagnosing liver nodules in computed tomography (CT) scans is addressed in this research by introducing a novel Computer-Aided Detection (CAD) system that makes use of an Efficient Network (EfficientNet) image classification algorithm. …”
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Classification of tomato leaf disease using Transductive Long Short-Term Memory with an attention mechanism by Aarthi Chelladurai, D.P. Manoj Kumar, S. S. Askar, Mohamed Abouhawwash, Mohamed Abouhawwash

“…However, effective harvesting still remains a major issue because tomatoes are easily susceptible to weather conditions and other types of attacks. …”
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Automatic Chest CT Image Findings of Novel Coronavirus Pneumonia (COVID-19) Using U-Net Based Convolutional Neural Network by S. Akila Agnes, J. Anitha, A. Arun Solomon

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LCFC-Laptop: A Benchmark Dataset for Detecting Surface Defects in Consumer Electronics by Hua-Feng Dai, Jyun-Rong Wang, Quan Zhong, Dong Qin, Hao Liu, Fei Guo

“…Annotations were then applied using bounding boxes for object detection and pixelwise masks for semantic segmentation. In addition to the dataset construction scheme, commonly used semantic segmentation methods were benchmarked using the provided mask annotations. …”
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Learning Omni-Dimensional Spatio-Temporal Dependencies for Millimeter-Wave Radar Perception by Hang Yan, Yongji Li, Luping Wang, Shichao Chen

“…We conducted extensive experiments using a diverse dataset of urban driving scenarios to characterize the sensor’s performance in multi-view semantic segmentation and object detection tasks. Experiments showed that U-MLPNet achieves competitive performance against state-of-the-art (SOTA) methods, improving the mAP by 3.0% and mDice by 2.7% in RD segmentation and AR and AP by 1.77% and 2.03%, respectively, in object detection. …”
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Masked Feature Modeling for Generative Self-Supervised Representation Learning of High-Resolution Remote Sensing Images by Shiyan Pang, Hanchun Hu, Zhiqi Zuo, Jia Chen, Xiangyun Hu

“…Extensive experiments involving main properties of the MFM for generative self-supervised learning, fine-tuning the MFM on the downstream semantic segmentation task, and comparisons with the other state-of-the-art generative self-supervised learning algorithms show that, through the combined advantages of the CNN and Transformer architectures, the proposed method has better feature extraction capability and higher accuracy on downstream tasks such as semantic segmentation.…”
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Clinical implications of dextrocardia based on four visceroatrial situs studies by Mao-Sheng Hwang, Ching-Chia Kuo, Chao-Jan Wang, Wen-Jen Su, Jaw-Ji Chu, Hung-Tao Chung, Hsiang-Ju Hsiao, Yi-Jung Chang

“…Methods: We retrospectively reviewed the medical records of 211 children with primary dextrocardia. We used a segmental approach to diagnose CHD. We then analyzed and compared the distribution of the above-mentioned issues among the four visceroatrial situs. …”
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Optimal performance design of bat algorithm: An adaptive multi‐stage structure by Helong Yu, Jiuman Song, Chengcheng Chen, Ali Asghar Heidari, Yuntao Ma, Huiling Chen, Yudong Zhang

“…The results show that the proposed BA‐based algorithm has apparent advantages, and it can effectively segment the disease spots from citrus leaves when the segmentation threshold is at a low level. …”
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Enhanced machine learning models for predicting three-year mortality in Non-STEMI patients aged 75 and above by Jing Zhang, Wuyu Xiong, Chengzhi Zhang, Cuiyuan Huang, Wenqiang Li, Li Liu, Wei Wang, Ye Sang, Huiling Zhen, Caiwei Tan, Jiajuan Yang, Jian Yang

“…Abstract Background Non-ST segment elevation myocardial infarction (Non-STEMI) is a severe cardiovascular condition mainly affecting individuals aged 75 and above, who are at higher risk of mortality due to age-related vulnerabilities and other health issues. …”
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Synchrotron-based 3D X-ray computed tomography reveals root system architecture: Plastic responses to phosphorus placement by Frederik J.T. van der Bom, Philipp D. Lösel, Andrew M. Kingston, Zhe H. Weng, Nelly S. Raymond, Anton Maksimenko, Daniel Hausermann, Michael J. Bell, Casey L. Doolette, Enzo Lombi, Peter M. Kopittke

“…Secondly, we developed a deep learning approach for segmentation and quantification of root length and diameter. …”
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An Enhanced and Unsupervised Siamese Network With Superpixel-Guided Learning for Change Detection in Heterogeneous Remote Sensing Images by Zhiyuan Ji, Xueqian Wang, Zhihao Wang, Gang Li

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Automatic Change Detection of High Resolution Remote Sensing Images Based on Level Set Evolution and Support Vector Machine Classification by YAN Ming, CAO Guo, XIA Meng

“…We propose a method for change detection in highresolution remote sensing images by means of level set evolution and Support Vector Machine (SVM) classification, which combined both pixellevel method and objectlevel method Both pixelbased change features and objectbased ones are extracted to improve the discriminability between the changed class and the unchanged classAt the pixellevel, the change detection problem is formulated as a segmentation issue using level set evolution in the difference image At the objectlevel, potential training samples are selectedfrom the segmentation results without manual intervention into SVM classifier Thereafter, the final changes are obtained by combining the pixelbased changes and the objectbased changes A chief advantage of our approach is being able to select appropriate samples for SVM classifier training Furthermore, our proposed method helps improving the accuracy and the degree of automation We systematically evaluated it with a variety of SPOT5 images and aerial images Experimental results demonstrated the accuracy of our proposed method…”
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Robust Classification via Finite Mixtures of Matrix Variate Skew-<i>t</i> Distributions by Abbas Mahdavi, Narayanaswamy Balakrishnan, Ahad Jamalizadeh

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VirtualPainting: Addressing Sparsity with Virtual Points and Distance-Aware Data Augmentation for 3D Object Detection by Sudip Dhakal, Deyuan Qu, Dominic Carrillo, Mohammad Dehghani Tezerjani, Qing Yang

“…We present an innovative approach that involves the generation of virtual LiDAR points using camera images and enhancing these virtual points with semantic labels obtained from image-based segmentation networks to tackle this issue and facilitate the detection of sparsely distributed objects, particularly those that are occluded or distant. …”
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Precise Feature Removal Method Based on Semantic and Geometric Dual Masks in Dynamic SLAM by Zhanrong Li, Chao Jiang, Yu Sun, Haosheng Su, Longning He

“…In visual Simultaneous Localization and Mapping (SLAM) systems, dynamic elements in the environment pose significant challenges that complicate reliable feature matching and accurate pose estimation. To address the issue of unstable feature points within dynamic regions, this study proposes a robust dual-mask filtering strategy that synergistically integrates semantic segmentation information with geometric outlier detection techniques. …”
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Ancient Character Recognition: A Comprehensive Review by R. Krithiga, S. R. Varsini, R. Gabriel Joshua, C. U. Om Kumar

“…Different models have been evaluated based on their segmentation and recognition rates, accuracy, detection rate, precision, and confusion matrix. …”
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