There is a scarcity of multilingual vision-language models that properly account for the perceptual differences that are reflected in image captions across languages and cultures. In this work, through a multimodal, m...
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Metaphors are everywhere. They appear extensively across all domains of natural language, from the most sophisticated poetry to seemingly dry academic prose. A significant body of research in the cognitivescience of ...
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Despite recent attention to depth for various tasks, it is still an unexplored modality for weakly-supervised object detection (WSOD). We propose an amplifier method for enhancing the performance of WSOD by integratin...
Despite recent attention to depth for various tasks, it is still an unexplored modality for weakly-supervised object detection (WSOD). We propose an amplifier method for enhancing the performance of WSOD by integrating depth information. Our approach can be applied to different WSOD methods based on multiple-instance learning, without necessitating additional annotations or inducing large computational cost. Our proposed method employs monocular depth estimation to obtain hallucinated depth information, which is then incorporated into a Siamese WSOD network using contrastive loss and fusion. By analyzing the relationship between language context and depth, we calculate depth priors to identify the bounding box proposals that may contain an object of interest. These depth priors are then utilized to update the list of pseudo ground-truth boxes, or adjust the confidence of per-box predictions. We evaluate our proposed method on three datasets (COCO, PASCAL VOC, and Conceptual Captions) by implementing it on top of two state-of-the-art WSOD methods, and we demonstrate a substantial enhancement in performance.
In light of unprecedented increases in the popularity of the internet and social media, comment moderation has never been a more relevant task. Semi-automated comment moderation systems greatly aid human moderatorsby ...
Tourism is one of Indonesia's main economic drivers because it can absorb many workers and bring in foreign exchange through tourism activities. Research related to Smart Tourism Destinations (STDs) and the techno...
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Existing object recognition models have been shown to lack robustness in diverse geographical scenarios due to domain shifts in design and context. Class representations need to be adapted to more accurately reflect a...
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ISBN:
(数字)9798350353006
ISBN:
(纸本)9798350353013
Existing object recognition models have been shown to lack robustness in diverse geographical scenarios due to domain shifts in design and context. Class representations need to be adapted to more accurately reflect an object concept under these shifts. In the absence of training data from target geographies, we hypothesize that geographically diverse descriptive knowledge of categories can enhance robustness. For this purpose, we explore the feasibility of probing a large language model for geography-based object knowledge, and we examine the effects of integrating knowledge into zero-shot and learnable soft prompting with CLIP. Within this exploration, we propose geog-raphy knowledge regularization to ensure that soft prompts trained on a source set of geographies generalize to an un-seen target set. Accuracy gains over prompting baselines on DollarStreet while training only on Europe data are up to +2.8/1.2/1.6 on target data from Africa/Asia/Americas, and +4.6 overall on the hardest classes. Competitive performance is shown vs. few-shot target training, and analysis is provided to direct future study of geographical robustness.
Research in the development of Hepatitis C disease prediction is increasingly developing, especially using machine learning models which is able to make predictions quickly and accurately. In this study, a comparison ...
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ISBN:
(数字)9798331517601
ISBN:
(纸本)9798331517618
Research in the development of Hepatitis C disease prediction is increasingly developing, especially using machine learning models which is able to make predictions quickly and accurately. In this study, a comparison of several classification methods was carried out by also applying feature reduction, NCA. In this study, a comparison of performance was carried out if the data was entered into the NCA feature extraction method with KNearest Neighborhood (KNN) and Support Vector Machine (SVM) and a comparison of performance if the data did not use the NCA feature extraction method. The performance comparison metrics used in the study were accuracy, sensitivity, specification, Matthews Correlation Coefficient (MCC), and Kappa value. The highest accuracy (99.36%), sensitivity (91.94%), specification (99.67%), MCC $(0.895)$ and the best Kappa value $(0.889)$ were obtained in the KNN-NCA prediction method.
– The demands of today’s 5G mobile network, especially low latency and high bandwidth, are a big challenge for the 5G Core (5GC) provider. The most critical user data packet handler in the 5GC Network Function (NF) ...
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ISBN:
(纸本)9788995004395
– The demands of today’s 5G mobile network, especially low latency and high bandwidth, are a big challenge for the 5G Core (5GC) provider. The most critical user data packet handler in the 5GC Network Function (NF) is the User Plane Function (UPF), which is responsible for moving data from the user equipment to the destination data network, and vice versa. Existing work mainly focuses on implementing UPF using the key technologies of high-speed data processing. In this paper, with a mobile core provider called free5GC for a standalone (SA) 5G network, we share our experience with the implementation of UPF by using a programmable hardware appliance, which can offer more Tbps compared to the implementation of software UPF that can offer only a few hundred Gbps. For that, we demonstrate how to build up a more flexible architecture of UPF by using the Software-Defined Networking (SDN) concept due to the opacity of protocol specification. We split the UPF control signal implementation into a software application, and user data packet processing into a programmable hardware appliance. We also show how to integrate a number of current UPF data plane free5GC implementations such as Data Plane Development Kit (DPDK), Linux kernel module, and SmartNIC. Furthermore, we analyze and make use of microservices to support the specific features of the UPF data plane that cannot be implemented in a programmable hardware appliance. We tested our free5GC mobile network and the new UPF design architecture that can run on a real programmable hardware appliance from Accton CSP-7551. The evaluation results show that our programmable user plane can reach the line rate. Copyright 2023 KICS.
Melanoma is a malignant form of cancer that affects the skin and has a particularly high mortality rate, so it requires early detection to increase the level of safety for users. Diagnosis and detection of skin cancer...
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The cognitive Agents and Interaction Lab (CAIL) at the University of Dhaka has strategically developed a focused High-Performance Computing (HPC) facility, underpinning its niche in artificial intelligence (AI) resear...
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