標(biāo)題: Titlebook: Advances in Visual Computing; 17th International S George Bebis,Bo Li,Remco Chang Conference proceedings 2022 The Editor(s) (if applicable) [打印本頁(yè)] 作者: Jaundice 時(shí)間: 2025-3-21 17:06
書目名稱Advances in Visual Computing影響因子(影響力)
書目名稱Advances in Visual Computing影響因子(影響力)學(xué)科排名
書目名稱Advances in Visual Computing網(wǎng)絡(luò)公開度
書目名稱Advances in Visual Computing網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Advances in Visual Computing被引頻次
書目名稱Advances in Visual Computing被引頻次學(xué)科排名
書目名稱Advances in Visual Computing年度引用
書目名稱Advances in Visual Computing年度引用學(xué)科排名
書目名稱Advances in Visual Computing讀者反饋
書目名稱Advances in Visual Computing讀者反饋學(xué)科排名
作者: 不要嚴(yán)酷 時(shí)間: 2025-3-21 21:22 作者: 臆斷 時(shí)間: 2025-3-22 01:03
V2F: Real Time Video Segmentation with?Apache Flinkies a series of operators in a pipeline to transform a video stream into shots. These operators are replicated to work in parallel on Flink-managed computing nodes. The V2F deployment of the standard twin-comparison video segmentation method is more than 7 times faster than its non-parallel (i.e., sequential) implementation.作者: 牛的細(xì)微差別 時(shí)間: 2025-3-22 06:42 作者: GUILT 時(shí)間: 2025-3-22 12:47 作者: Graduated 時(shí)間: 2025-3-22 16:30
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/150127.jpg作者: 外貌 時(shí)間: 2025-3-22 19:42
Davide Del Curto,Maria Paola Borgarino that are affected by encephalopathy lose their mass due to the injury. Thus, quantifying neurodevelopmental changes is often performed using 2D approaches where the neuroradiologist performs fiducial landmarks to monitor clinical outcomes. We showed how non-rigid correspondence analysis allows rele作者: 熟練 時(shí)間: 2025-3-23 01:05
Maria Paola Borgarino,Davide Del Curtoelop and train a biomimetic, SNN-driven, neuromuscular oculomotor controller for a realistic biomechanical model of the human eye. Event-based data flow in the SNN directs the necessary extraocular-muscle-actuated eye movements. We train our SNN models from scratch using modified deep learning techn作者: Acetabulum 時(shí)間: 2025-3-23 01:49
Conserving 20th-Century Architecture progress in terms of the ability of machine vision systems to carry out object segmentation, but this work has ignored ., or the determination for a given edge of which side the object is that owns it. Here we present a method for determining border ownership using a deep neural network model. Addi作者: 貝雷帽 時(shí)間: 2025-3-23 07:38 作者: voluble 時(shí)間: 2025-3-23 12:56 作者: 桉樹 時(shí)間: 2025-3-23 16:17 作者: 聯(lián)想 時(shí)間: 2025-3-23 18:20 作者: PON 時(shí)間: 2025-3-23 23:05
Zanisah Man,Sharina Abdul Halimbeing sold, just to name a few of them. As a seller, it is absolutely essential to price the property competitively else it will not attract any buyers. This problem has given rise to multiple companies as well as past research works that try to enhance the predictability of property prices using re作者: 消耗 時(shí)間: 2025-3-24 03:36
Nathan N. Gichuki,Jane M. Macharia-spectral data set is amenable to computational algorithms that highlight functional properties of the sample. Although Fourier transform IR (FT-IR) imaging provides reliable analytical information over a wide spectral profile, long data acquisition times are a major challenge impeding broad adoptab作者: PON 時(shí)間: 2025-3-24 10:22 作者: intangibility 時(shí)間: 2025-3-24 13:35 作者: 緩和 時(shí)間: 2025-3-24 18:19
https://doi.org/10.1007/978-3-030-26407-9ies a series of operators in a pipeline to transform a video stream into shots. These operators are replicated to work in parallel on Flink-managed computing nodes. The V2F deployment of the standard twin-comparison video segmentation method is more than 7 times faster than its non-parallel (i.e., s作者: Legion 時(shí)間: 2025-3-24 20:12
https://doi.org/10.1007/978-3-030-26407-9h as pose, illumination, viewpoint, background, and sensor noise. Recent approaches postulate that powerful architectures have the capacity to learn feature representations invariant to nuisance factors, by training them with losses that minimize intra-class variance and maximize inter-class separat作者: 驚惶 時(shí)間: 2025-3-25 01:03
https://doi.org/10.1007/978-3-030-26407-9o function correctly. While previous state-of-the-art methods relied on modeling social interactions with LSTMs, with videos captured with a static camera from a bird’s-eye view, our paper presents a new method that leverages the Transformers architecture and offers a reliable way to model future tr作者: 刪減 時(shí)間: 2025-3-25 06:31
Maria Apostolopoulou,Antonia Moropoulouns one of the most used clinical tests to this day. Despite the swinging flashlight test’s straightforward approach, a number of factors can add variability into the clinical methodology and reduce the measurement’s validity and reliability. This includes small and poorly responsive pupils, dark iri作者: 不整齊 時(shí)間: 2025-3-25 10:06
Maria Paola Borgarino,Davide Del Curtoiques. We use surrogate gradients and introduce a linear layer to convert membrane voltages from the final spiking layer into the desired outputs. Our SNN foveation network enhances the biomimetic properties of the virtual eye model and enables it to perform reliable visual tracking.作者: 卡死偷電 時(shí)間: 2025-3-25 13:03 作者: contrast-medium 時(shí)間: 2025-3-25 16:44 作者: Presbycusis 時(shí)間: 2025-3-25 20:32 作者: CESS 時(shí)間: 2025-3-26 01:56 作者: WATER 時(shí)間: 2025-3-26 07:31 作者: Ambulatory 時(shí)間: 2025-3-26 08:28
Conference proceedings 2022hich was held in October 2022.?.The 61 papers presented in these volumes were carefully reviewed and selected from 110 submissions. They are organized in the following topical sections:?.Part I: ?deep learning I; visualization; object detection and recognition; deep learning II; video analysis and e作者: 有機(jī)體 時(shí)間: 2025-3-26 15:40
Fire Alarms as Urban Social Indicatorsndtruth. In our benchmark, several performance metrics are leveraged to compare the results of different methods with the groundtruth. The experiments provide insightful results which demonstrate the effectiveness of inpainting methods in this particular problem.作者: 有效 時(shí)間: 2025-3-26 16:51 作者: intoxicate 時(shí)間: 2025-3-26 22:27
Photobombing Removal Benchmarkingndtruth. In our benchmark, several performance metrics are leveraged to compare the results of different methods with the groundtruth. The experiments provide insightful results which demonstrate the effectiveness of inpainting methods in this particular problem.作者: 一再煩擾 時(shí)間: 2025-3-27 02:14
Saliency Can Be All You Need in?Contrastive Self-supervised Learningive SSL algorithms subject to standard augmentation techniques. This evaluation, which was conducted across multiple datasets, indicated that the proposed technique indeed contributes to SSL. We hypothesize whether salient image segmentation may suffice as the only augmentation policy in Contrastive SSL when treating downstream segmentation tasks.作者: 附錄 時(shí)間: 2025-3-27 07:36 作者: 過(guò)多 時(shí)間: 2025-3-27 12:21 作者: 性上癮 時(shí)間: 2025-3-27 17:27
Border Ownership, Category Selectivity and Beyondgiven edge of which side the object is that owns it. Here we present a method for determining border ownership using a deep neural network model. Additionally, the model learns selectivity for object categories, suggesting a potential relationship between border ownership information and object category-selectivity. ..作者: 混亂生活 時(shí)間: 2025-3-27 18:42 作者: 偏狂癥 時(shí)間: 2025-3-27 23:41
Sparse Kernel Transfer Learningng, a method that utilizes sparse coding and dictionary learning to pre-train the filters of a CNN. This pre-training is reminiscent of the unsupervised autoencoder training that used to be performed when stacking layers of a neural network. We argue that this dictionary transfer provides a better i作者: 清楚 時(shí)間: 2025-3-28 02:16
Automatic Detection and?Recognition of?Products and?Planogram Conformity Analysis in?Real Time on?State in real time..The proposed method was validated with a dataset of 385 shelf images of 12 product categories from several stores of four different brands. Experimental results show that our approach is highly accurate in finding a product in all categories and for solving planogram conformity rat作者: 悅耳 時(shí)間: 2025-3-28 09:26 作者: Debility 時(shí)間: 2025-3-28 11:36
House Price Prediction via Visual Cues and Estate Attributesng the dataset collection, different features are extracted from the input data. Furthermore, a multi-kernel regression approach is used to predict the house price from both visual cues and estate attributes. The extensive experiments demonstrate the superiority of the proposed method over the basel作者: Terminal 時(shí)間: 2025-3-28 18:09 作者: 易受刺激 時(shí)間: 2025-3-28 21:52
Joint Discriminative and?Metric Embedding Learning for?Person Re-identificationroxy for the missing gradients. We further improve invariance to nuisance factors by adding the discriminative task of predicting attributes. Our extensive evaluation highlights that when only a holistic representation is learned, we consistently outperform the state-of-the-art on the three most cha作者: hangdog 時(shí)間: 2025-3-29 01:08 作者: 間諜活動(dòng) 時(shí)間: 2025-3-29 05:49
VR-SFT: Reproducing Swinging Flashlight Test in?Virtual Reality to?Detect Relative Afferent Pupillarach to the swinging flashlight exam, VR-SFT, by making use of virtual reality (VR). We suggest that the clinical records of the subjects and the results of VR-SFT are comparable. In this paper, we describe how we exploit the features of immersive VR experience to create a reliable and objective swin作者: 混合物 時(shí)間: 2025-3-29 08:15 作者: 扔掉掐死你 時(shí)間: 2025-3-29 11:51
https://doi.org/10.1007/978-1-4684-4031-7ng, a method that utilizes sparse coding and dictionary learning to pre-train the filters of a CNN. This pre-training is reminiscent of the unsupervised autoencoder training that used to be performed when stacking layers of a neural network. We argue that this dictionary transfer provides a better i作者: Saline 時(shí)間: 2025-3-29 19:14
Conserving America’s Neighborhoodsate in real time..The proposed method was validated with a dataset of 385 shelf images of 12 product categories from several stores of four different brands. Experimental results show that our approach is highly accurate in finding a product in all categories and for solving planogram conformity rat作者: 戰(zhàn)役 時(shí)間: 2025-3-29 23:22
Fire Alarms as Urban Social Indicatorsthe original location. To evaluate our approach experimentally, we obfuscate faces from various datasets by applying blurring, pixelation and the proposed technique. To determine the success of obfuscation, we verify whether the original and the resulting face represent the same person using a state作者: NAIVE 時(shí)間: 2025-3-30 00:38 作者: chemical-peel 時(shí)間: 2025-3-30 05:12 作者: generic 時(shí)間: 2025-3-30 12:09
https://doi.org/10.1007/978-3-030-26407-9roxy for the missing gradients. We further improve invariance to nuisance factors by adding the discriminative task of predicting attributes. Our extensive evaluation highlights that when only a holistic representation is learned, we consistently outperform the state-of-the-art on the three most cha作者: 骨 時(shí)間: 2025-3-30 15:34
https://doi.org/10.1007/978-3-030-26407-9 in a simple way, modeling each target’s trajectory separately, without the use of complex social interactions between humans or interactions between targets and the scene. Experimental results show that our method overall outperforms previous state-of-the-art methods, and yields better results in c作者: Cabinet 時(shí)間: 2025-3-30 19:32 作者: modifier 時(shí)間: 2025-3-30 22:22 作者: integral 時(shí)間: 2025-3-31 03:09
Biomimetic Oculomotor Control with?Spiking Neural Networkselop and train a biomimetic, SNN-driven, neuromuscular oculomotor controller for a realistic biomechanical model of the human eye. Event-based data flow in the SNN directs the necessary extraocular-muscle-actuated eye movements. We train our SNN models from scratch using modified deep learning techn作者: irreparable 時(shí)間: 2025-3-31 07:30 作者: 控制 時(shí)間: 2025-3-31 10:18 作者: DUST 時(shí)間: 2025-3-31 16:13
Photobombing Removal Benchmarking remove the photobombing from taken images to produce a pleasing image. In this paper, the aim is to conduct a benchmark on this aforementioned problem. To this end, we first collect a dataset of images with undesired and distracting elements which requires the removal of photobombing. Then, we anno
