Riassunto. Costruita verso il 110/100 a.C. da Quinto Mucio Scevola il Pontefíce Massimo e affrescata in secondo stile nel 40 a. C. per volontà di suo ñipóte omonimo, la 'Villa del Giurista' si ...distingue per la qualità dei frammenti, che alternano temi decorativi e mitologici con rappresentazioni, di potente realismo, degli strumenti quotidiani del diritto praticato e con la celebre Formula Mucci Scaevlae. Gli affreschi vengono letti alia luce da un lato del tentativo di pacificazione del 40-39, dall'altro di esaltazione in chiave stoica della rusticitas come ritorno alie origini romane, dall'altro ancora come inizio di quello stile iperrealistico e illusionistico che sará proprio dell'età augustea (Villa di Livia Drusilla a Prima Porta) e soprattutto neroniana, con Popera di Fabullo a Roma e a Oplontis; ponendo cosi in termini nuovi il rapporto fra persona, spazio e figurazione.
Nowadays, bots can be seen everywhere on the Internet and are responsible for a large percentage of website traffic. The problem of bot detection has increasingly gained attention since more and more ...bots have been abused from click fraud in online advertisements to launching credential stuffing attacks for harvesting user accounts at a large scale. In this work, we present an end-to-end deep framework for bot detection based on computer mouse movements. Specifically, we propose a novel visual representation scheme that can simultaneously encode spatial and kinematic information in mouse movements into an image which can then be used as the input to Convolutional Neural Networks (CNN). Various strategies to encode kinematic features into images are investigated to obtain a better scheme of visual representation. Experimental results show that the proposed representation scheme in combination with CNN outperforms several baseline models with a TPR of 99.34% in detecting known bots and can be generalized to unknown bots with a highest accuracy of 99.20%. We also demonstrate that the proposed approach can reach acceptable performance levels even for models trained with a small number of training samples. This makes the deployment of our approach easier in real-world scenarios.
•A deep learning framework for bot detection using mouse movements is presented.•A representation scheme that encodes spatial and kinematic information is proposed.•The proposed approach outperforms various baselines in bot detection via mouse data.
Self-supervised visual representation learning (SSL) attempts to extract significant features from unlabeled datasets, alleviating the necessity for labor-intensive and time-consuming manual labeling ...processes. However, existing contrastive learning-based methods typically suffer from the underutilization of datasets, consume significant computational resources, and employ longer training epochs or large batch sizes. In this study, we propose a novel method aimed at optimizing self-supervised learning that integrates the advantages of sparse-dense sampling and collaborative optimization, thereby significantly improving the performance of downstream tasks. Specifically, sparse-dense sampling primarily focuses on high-level semantic features, while leveraging the spatial structure relationship provided by the unlabeled dataset to ensure the incorporation of low-level texture features to improve data utilization. Besides, collaborative optimization, including contrastive and location tasks, further enhances the model’s ability to perceive features of different dimensions, thereby improving its utilization of features in the embedding space. Furthermore, the combination of sparse-dense sampling and collaborative optimization strategies can reduce computational consumption while improving performance. Extensive experiments demonstrate that the proposed method effectively reduces the computational requirements while delivering favorable results. The codes and model weights will be available at https://github.com/AI-TYQ/S4.
While deep learning has become a key ingredient in the top performing methods for many computer vision tasks, it has failed so far to bring similar improvements to instance-level image retrieval. In ...this article, we argue that reasons for the underwhelming results of deep methods on image retrieval are threefold: (1) noisy training data, (2) inappropriate deep architecture, and (3) suboptimal training procedure. We address all three issues. First, we leverage a large-scale but noisy landmark dataset and develop an automatic cleaning method that produces a suitable training set for deep retrieval. Second, we build on the recent R-MAC descriptor, show that it can be interpreted as a deep and differentiable architecture, and present improvements to enhance it. Last, we train this network with a siamese architecture that combines three streams with a triplet loss. At the end of the training process, the proposed architecture produces a global image representation in a single forward pass that is well suited for image retrieval. Extensive experiments show that our approach significantly outperforms previous retrieval approaches, including state-of-the-art methods based on costly local descriptor indexing and spatial verification. On Oxford 5k, Paris 6k and Holidays, we respectively report 94.7, 96.6, and 94.8 mean average precision. Our representations can also be heavily compressed using product quantization with little loss in accuracy.
Semi-Supervised and Unsupervised Deep Visual Learning: A Survey Chen, Yanbei; Mancini, Massimiliano; Zhu, Xiatian ...
IEEE transactions on pattern analysis and machine intelligence,
2024-March, 2024-Mar, 2024-3-00, 20240301, Letnik:
46, Številka:
3
Journal Article
Recenzirano
Odprti dostop
State-of-the-art deep learning models are often trained with a large amount of costly labeled training data. However, requiring exhaustive manual annotations may degrade the model's generalizability ...in the limited-label regime.Semi-supervised learning and unsupervised learning offer promising paradigms to learn from an abundance of unlabeled visual data. Recent progress in these paradigms has indicated the strong benefits of leveraging unlabeled data to improve model generalization and provide better model initialization. In this survey, we review the recent advanced deep learning algorithms on semi-supervised learning (SSL) and unsupervised learning (UL) for visual recognition from a unified perspective. To offer a holistic understanding of the state-of-the-art in these areas, we propose a unified taxonomy. We categorize existing representative SSL and UL with comprehensive and insightful analysis to highlight their design rationales in different learning scenarios and applications in different computer vision tasks. Lastly, we discuss the emerging trends and open challenges in SSL and UL to shed light on future critical research directions.
This essay analyses Dorothy Cross's 2003 video work Medusae in relation to late-twentieth-century literary reworkings of the historical past A visual representation of the obscure woman naturalist ...Maude Delap, Medusae is argued here to function as historiographic montage, interrogating and celebrating the possibility of visualising an historical life through visual art. Using established literary models including intertextuality and dialogic structuring, the essay presents Medusae as an important example of visual art's response to debates surrounding historiography and creative representations of the past through making a detail analysis of how its elements and forms mediate a specific historical life in 'the present'.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
This study aims to develop an assessment instrument to measure students' critical thinking and visual representation abilities in optical instrument material. This research and development (RD) ...employed the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) instructional model. This research develops a test instrument that has more specific stages so the ADDIE development stage is integrated with the development stage of the test instrument developed by Mardapi. The subjects in this study are grade XI students of State Madrasah Aliyah (MAN) 4 Bantul. This study produced a test instrument for measuring students' critical thinking and visual representation abilities, with high validity,and analyzed using Aiken's V. The items for assessing critical thinking and visual representation abilities were analyzed using the QUEST program with the following findings. (1) The analysis results of instrument validation using Aiken's V obtained an average Aiken's Value above 0.4 with high validity and moderate validity criteria so all items are valid. (2) The pre-test analysis on item estimates obtained MNSQ Infit in the range 0.77-1.30 and the value of outfit t ≤ 2 and in the MNSQ Infit case estimates in the range 0.77-1.30, so overall, the items matched to Rasch models. (3) Post-test analysis on item estimates obtained MNSQ Infit in the range 0.77-1.30 and outfit t value ≤ 2 and in case estimates MNSQ Infit in the range 0.77-1.30 so, overall, items are in accordance with Rasch models. (4) The reliability of the pre-test items is 0.92 while the reliability of the post-test items is 0.76. (5) The difficulty level of the items in the pre-test results shows that Question 10 is the most difficult while number 3 is the easiest, and in the post-test results, Question 8 is the most difficult while Question 6 is the easiest.
The paper, relying on Marxist and Lacanian psychoanalytic theories, fosters several ways to apprehend non-mimetic characterization in Dickens’ Dombey and Son by theorizing the ways in which ...aesthetic, political, historical ideologies articulate themselves in means of representation. Since the influence of the visual arts on the novel is central for my argument, this paper attempts to give substantial critical consideration to Dickens’ representation of images and their double meaning that help understand social ideological relations in the bourgeois society. Visual representation, as a metaphor for the role of materiality in characterization throughout Dickens’ work and the role of fetishes, depicts the reification of the subject under capitalism. Visualization technique captures the flux of shaping characters and their function in everyday life. This aesthetic technique has led to reevaluation of Dickens’s use of visuals as a unique feature in fiction of the highest quality. Hence, representations of the inward life in fiction are merely linguistic approximations of something which cannot be wholly captured in language.
PDF
