Search Results - spatial information from detection framework

VS-BIM: a cognitive map-driven framework enhancing MLLM for automatic safety inspection in construction by Wang, Lei, Liu, Yu, Wang, Cunrui, An, Hongda, Li, Yiting

“…To address this, we propose VS-BIM, a generative zero-shot framework driven by cognitive maps. We reconstruct 3D scenes from panoramic video and Building Information Models (BIM), and align visual and semantic information into a queryable 3D cognitive map that serves as the spatial working memory for MLLMs. …”
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Passive client-centric rogue access point detection framework for WiFi hotspots by Ahmad, Nazrul Muhaimin

“…The proliferation of Wi-Fi hotspots in public places provides seamless Internet connectivity anywhere at any time to the wireless clients.Although many hotspots are often unprotected,unmanaged and unencrypted,this does not prevent the clients from actively connecting to the network.The underlying problem is that the network Access Point (AP) is always trusted.The adversary can impersonate a legitimate AP by setting up a rogue AP to commit espionage and to launch evil-twin attack,session hijacking,and eavesdropping.To aggravate the threats, existing detection solutions are ill-equipped to safeguard the client against rogue AP.Infrastructure- centric solutions are heavily relied on the deployment of sensors or centralized server for rogue AP detection, which are limited,expensive and rarely to be implemented in hotspots.Even though client-centric solutions offer threat-aware protection for the client,but the dependency of the existing solutions on the spoofable contextual network information and the necessity to be associated with the network makes those solutions are not viable for the hotspot’s client.Hence,this work proposes a framework of passive client-centric rogue AP detection for hotspots.Unlike existing solutions,the key idea is to piggyback AP-specific and network-specific information in IEEE 802.11 beacon frame that enables the client to perform the detection without authentication and association to any AP.Based on the spatial fingerprints included in the broadcasted information from the APs in the vicinity of the client,this work discloses a novel concept that enables the rogue AP detection via the client’s ability to self-colocalize and self-validate its own position in the hotspot.The legitimacy of the APs in the hotspot,in this view,lies in the fact that the correct matching between the Received Signal Strength Indicator (RSSI) measurements at the client and pre-recorded fingerprints is attainable when the beacons are transmitted only from the legitimate APs.Hence,any anomalousness in AP’s beacon frame or any attempt to replay the legitimate AP’s beacon frame from different location can be detected and classified as rogue AP threats.Through experiments in real environment,the results demonstrate that with proper algorithm selection and parameters tuning,the rogue AP detection framework can achieve over 90% detection accuracy in classifying the absence and presence of rogue AP threats in the hotspot.…”
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Moving objects detection from UAV captured videos using trajectories of matched regional adjacency graphs by Harandi, Bahareh Kalantar Ghorashi

“…This thesis deals with the topic of moving object detection (MOD) whose intention is to identify and detect single or multiple moving objects from video. …”
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Five-Class SSVEP Response Detection using Common Spatial Pattern (CSP)-SVM Approach by Rashid, Mamunur, Norizam, Sulaiman, Mahfuzah, Mustafa, Bari, Bifta Sama

“…This paper represents the feature extraction and classification frameworks to detect five classes EEG-SSVEP responses. …”
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Coherent crowd analysis with visual attributes / Nurul Japar by Nurul , Japar

“…Third, this thesis extends the coherent group detection framework towards scene understanding. Specifically, a collectiveness analysis framework is designed to quantify and detect collectiveness from individual-level to scene level. …”
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GIS Smart Mapping Technique For Urban Spatial Pattern Analysis - A Case Study On Nibong Tebal Sub-District by Ahmad, Ramlah

“…In conclusion, this research provides useful results in demonstrating a process of integrating information derived from satellite imagery with other spatial data in land use change detection study.…”
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Large-scale detection, mapping, and initial health assessment of date palm trees using multiplatform remotely-sensed data and deep learning techniques by Gibril, Mohamed Barakat Abdelfatah

“…The proposed framework also exhibits great generalizability in detecting and mapping individual date palm trees from different UAV images with diverse spatial resolutions. …”
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Smile detection using hybrid face representation by Arigbabu, Olasimbo Ayodeji, Mahmood, Saif, Syed Ahmad Abdul Rahman, Sharifah Mumtazah, Arigbabu, Abayomi A.

“…By locally weighting the descriptors from very dense patches of the image, we induce discriminating local spatial context to the distribution of the descriptions from the face image. …”
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Efficient NASNetMobile-enhanced Vision Transformer for weakly supervised video anomaly detection by Arif Mohamad, Muhammad Luqman, Abd Rahman, Mohd Amiruddin, Mohd Shah, Nurisya, Kumar Sangaiah, Arun

“…This research presents NASNetMobile–EViT, a lightweight framework that addresses both the computational burden and the contextual information deficiency that hinder weakly supervised anomaly detection. …”
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Testing the minimal bounded space method on vision-based drone navigation / Yap Seng Kuang by Yap , Seng Kuang

“…There is no imaging involved, but the laser sensor does record depth information. The spatial openings are derived by analyzing occlusion information from the environment, which is available from the depth information. …”
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Steel strips surface classification and defect detection based on multiple integrated features and classification schemes by Ashour, Mohammed W. M.

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Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

“…To extract the appearance based and structural information, each frame of the action sequences is evaluated for spatial features. …”
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Development of geospatial model for tuberculosis prediction in Gombak, Selangor, Malaysia by Mohidem, Nur Adibah

“…Methodology: The sociodemographic data of 3325 cases of TB such as age, gender, race, nationality, country of origin, educational level, employment status, health care worker status, income status, residency, and smoking status from January 2013 to December 2017 in Gombak were collected from the MyTB web and Tuberculosis Information System (TBIS) file. …”
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Computed tomography and echocardiography image fusion technique for cardiac images by Kalahroodi, Samaneh Mazaheri

“…The goal of this thesis is integrating detected features, segmentation result information, and intensity information from two mentioned images, into a non-rigid registration framework, and achieve a high quality spatial mapping. …”
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Leveraging sMRI, Self-Attention Mechanisms, and Evolving Spiking Neural Networks for Enhanced Suicide Ideation Detection in Depressed Young Adults by Corrine, Francis, Abdulrazak Yahya, Saleh

“…Furthermore, the study incorporates a user-centric evaluation framework that enables mental health professionals and service users to assess the model's detections and rationale, facilitating informed decision-making processes. …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

“…The proposed functions for the offline phase are the detection of spatial and spatiotemporal outliers and the macro clustering. …”
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Development Of Stereo-Matching Algorithm Based On Adaptive Weighted Prediction by Abd Razak, Siti Safwana

“…The experimental result on the proposed algorithm is able to reduce 17.4% of weighted average error for all and 9.62% of weighted average error for nonocc (nonoccluded) compared to others Stereo Matching Algorithm without the proposed framework. This framework experimental result was also compared with other methods which located in standard benchmarking dataset from the Middlebury. …”
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Development of river water level estimation from surveillance cameras for flood monitoring system using deep learning techniques by Muhadi, Nur 'Atirah

“…In Malaysia, a telemetric forecasting system is currently been used in flood monitoring systems. However, data information obtained from this system is one spatial dimension and one point-based station, thus it cannot represent the dynamics of the surface water extent. …”
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Analyzing Burglary Dynamics through Land Use in Selangor, Kuala Lumpur, and Putrajaya : A Space-Time EHSA Approach by Azizul, Ahmad, Tarmiji, Masron, Syahrul Nizam, Junaini, Mohd Azizul Hafiz, Jamian, Mohamad Hardyman, Barawi, Yoshinari, Kimura, Norita, Jubit, Ruslan, Rainis

“…The results reveal a nuanced spatial clustering of burglary incidents that is significantly influenced by varied land use types—ranging from residential and industrial zones to open spaces—thereby enhancing the granularity of hotspot detection and offering empirical insights into the temporal evolution of crime patterns. …”
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Wifi-based location-independent human activity recognition and localization using deep learning by Abuhoureyah, Fahd Saad Amed

“…Precise activity recognition and incorporation of through-wall sensing capabilities are achieved within the deep learning framework. Second, Multi-head Attention Mechanism Networks capture intricate patterns in Channel State Information (CSI) data, enhancing recognition accuracy for human activities detected through WiFi signals. …”
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