Oil spills represent significant environmental hazards in ocean ecosystems, requiring rapid and accurate detection and response mechanisms. Due to its efficacy, synthetic aperture radar (SAR) is an important tool for ...
详细信息
Flood disasters pose significant threats to human lives and infrastructure, necessitating advanced methods for the timely and accurate monitoring of water levels in rivers. This study introduces an innovative approach...
详细信息
Video portrait segmentation(VPS), aiming at segmenting prominent foreground portraits from video frames, has received much attention in recent years. However, the simplicity of existing VPS datasets leads to a limitat...
详细信息
Video portrait segmentation(VPS), aiming at segmenting prominent foreground portraits from video frames, has received much attention in recent years. However, the simplicity of existing VPS datasets leads to a limitation on extensive research of the task. In this work, we propose a new intricate large-scale multi-scene video portrait segmentation dataset MVPS consisting of 101 video clips in 7 scenario categories,in which 10843 sampled frames are finely annotated at the pixel level. The dataset has diverse scenes and complicated background environments, which is the most complex dataset in VPS to our best *** the observation of a large number of videos with portraits during dataset construction, we find that due to the joint structure of the human body, the motion of portraits is part-associated, which leads to the different parts being relatively independent in motion. That is, the motion of different parts of the portraits is imbalanced. Towards this imbalance, an intuitive and reasonable idea is that different motion states in portraits can be better exploited by decoupling the portraits into parts. To achieve this, we propose a part-decoupling network(PDNet) for VPS. Specifically, an inter-frame part-discriminated attention(IPDA)module is proposed which unsupervisedly segments portrait into parts and utilizes different attentiveness on discriminative features specified to each different part. In this way, appropriate attention can be imposed on portrait parts with imbalanced motion to extract part-discriminated correlations, so that the portraits can be segmented more accurately. Experimental results demonstrate that our method achieves leading performance with the comparison to state-of-the-art methods.
With the adoption of foundation models(FMs),artificial intelligence(AI) has become increasingly significant in bioinformatics and has successfully addressed many historical challenges,such as pre-training frameworks,m...
详细信息
With the adoption of foundation models(FMs),artificial intelligence(AI) has become increasingly significant in bioinformatics and has successfully addressed many historical challenges,such as pre-training frameworks,model evaluation and *** demonstrate notable proficiency in managing large-scale,unlabeled datasets,because experimental procedures are costly and labor *** various downstream tasks,FMs have consistently achieved noteworthy results,demonstrating high levels of accuracy in representing biological entities.A new era in computational biology has been ushered in by the application of FMs,focusing on both general and specific biological *** this review,we introduce recent advancements in bioinformatics FMs employed in a variety of downstream tasks,including genomics,transcriptomics,proteomics,drug discovery and single-cell *** aim is to assist scientists in selecting appropriate FMs in bioinformatics,according to four model types:language FMs,vision FMs,graph FMs and multimodal *** addition to understanding molecular landscapes,AI technology can establish the theoretical and practical foundation for continued innovation in molecular biology.
— In recent years, significant efforts have been dedicated to detect human emotions. This interest primarily stems from the fact that emotions influence individuals' reactions and behaviors. Understanding these i...
详细信息
In order to build realistic digital-twin systems, this paper proposes a novel two-stage algorithm for high-quality digital-twin services in cloud-assisted multi-tier networks. In our proposed algorithm, the first stag...
详细信息
Wireless Sensor Networks (WSNs) play an important role in the modern era and security has become an important research area. Intrusion Detection System (IDS) improve network security by monitoring the network state so...
详细信息
Let P be a set of points in the plane and let T be a maximum-weight spanning tree of P. For an edge (p, q), let Dpq be the diametral disk induced by (p, q), i.e., the disk having the segment pq as its diameter. Let DT...
详细信息
Autism spectrum disorder(ASD)is a multifaceted neurological developmental condition that manifests in several *** all autistic children remain undiagnosed before the age of *** problems affecting face features are oft...
详细信息
Autism spectrum disorder(ASD)is a multifaceted neurological developmental condition that manifests in several *** all autistic children remain undiagnosed before the age of *** problems affecting face features are often associated with fundamental brain *** facial evolution of newborns with ASD is quite different from that of typically developing *** recognition is very significant to aid families and parents in superstition and *** facial features from typically developing children is an evident manner to detect children analyzed with ***,artificial intelligence(AI)significantly contributes to the emerging computer-aided diagnosis(CAD)of autism and to the evolving interactivemethods that aid in the treatment and reintegration of autistic *** study introduces an Ensemble of deep learning models based on the autism spectrum disorder detection in facial images(EDLM-ASDDFI)*** overarching goal of the EDLM-ASDDFI model is to recognize the difference between facial images of individuals with ASD and normal *** the EDLM-ASDDFI method,the primary level of data pre-processing is involved by Gabor filtering(GF).Besides,the EDLM-ASDDFI technique applies the MobileNetV2 model to learn complex features from the pre-processed *** the ASD detection process,the EDLM-ASDDFI method uses ensemble techniques for classification procedure that encompasses long short-term memory(LSTM),deep belief network(DBN),and hybrid kernel extreme learning machine(HKELM).Finally,the hyperparameter selection of the three deep learning(DL)models can be implemented by the design of the crested porcupine optimizer(CPO)*** extensive experiment was conducted to emphasize the improved ASD detection performance of the EDLM-ASDDFI *** simulation outcomes indicated that the EDLM-ASDDFI technique highlighted betterment over other existing models in terms of numerous performance measures.
With the growing popularity of the Internet, digital images are used and transferred more frequently. Although this phenomenon facilitates easy access to information, it also creates security concerns and violates int...
详细信息
暂无评论