Search results for: VEHICLE DETECTION, TRAFFIC MONITORING SYSTEM, BACKGROUND SUBTRACTION, CONVOLUTIONAL NEURAL NETWORK - Bridge of Knowledge

Search

Search results for: VEHICLE DETECTION, TRAFFIC MONITORING SYSTEM, BACKGROUND SUBTRACTION, CONVOLUTIONAL NEURAL NETWORK

Best results in : Research Potential Pokaż wszystkie wyniki (104)

Search results for: VEHICLE DETECTION, TRAFFIC MONITORING SYSTEM, BACKGROUND SUBTRACTION, CONVOLUTIONAL NEURAL NETWORK

  • Zespół Systemów Multimedialnych

    * technologie archiwizacji, rekonstrukcji i dostępu do nagrań archiwalnych * technologie inteligentnego monitoringu wizyjnego i akustycznego * multimedialne technologie telemedyczne * multimodalne interfejsy komputerowe

  • Zespół Systemów Multimedialnych

    * technologie archiwizacji, rekonstrukcji i dostępu do nagrań archiwalnych * technologie inteligentnego monitoringu wizyjnego i akustycznego * multimedialne technologie telemedyczne * multimodalne interfejsy komputerowe

  • Zespół Systemów Decyzyjnych i Robotyki

    Automatyka i Robotyka, która posiada silne posadowienie w matematycznej Teorii Systemów i Teorii Sterowania, już w połowie ubiegłego stulecia zaistniała w powszechnej świadomości jako Cybernetyka, która – kontynuując czerpanie wiedzy ze zjawisk istniejących w świecie natury – przekształciła się w Sztuczną Inteligencję, ciągle nie przestaje być dynamicznie rozwijającą się dziedziną z gruntu interdyscyplinarną, łączącą wiedzę i umiejętności...

Best results in : Business Offer Pokaż wszystkie wyniki (28)

Search results for: VEHICLE DETECTION, TRAFFIC MONITORING SYSTEM, BACKGROUND SUBTRACTION, CONVOLUTIONAL NEURAL NETWORK

Other results Pokaż wszystkie wyniki (434)

Search results for: VEHICLE DETECTION, TRAFFIC MONITORING SYSTEM, BACKGROUND SUBTRACTION, CONVOLUTIONAL NEURAL NETWORK

  • Vehicle detector training with labels derived from background subtraction algorithms in video surveillance

    Publication

    - Year 2018

    Vehicle detection in video from a miniature station- ary closed-circuit television (CCTV) camera is discussed in the paper. The camera provides one of components of the intelligent road sign developed in the project concerning the traffic control with the use of autonomous devices being developed. Modern Convolutional Neural Network (CNN) based detectors need big data input, usually demanding their manual labeling. In the presented...

  • Vehicle Detection with Self-Training for Adaptative Video Processing Embedded Platform

    Publication

    Traffic monitoring from closed-circuit television (CCTV) cameras on embedded systems is the subject of the performed experiments. Solving this problem encounters difficulties related to the hardware limitations, and possible camera placement in various positions which affects the system performance. To satisfy the hardware requirements, vehicle detection is performed using a lightweight Convolutional Neural Network (CNN), named...

    Full text available to download

  • Style Transfer for Detecting Vehicles with Thermal Camera

    Publication

    - Year 2019

    In this work we focus on nighttime vehicle detection for intelligent traffic monitoring from the thermal camera. To train a Convolutional Neural Network (CNN) detector we create a stylized version of COCO (Common Objects in Context) dataset using Style Transfer technique that imitates images obtained from thermal cameras. This new dataset is further used for fine-tuning of the model and as a result detection accuracy on images...

  • 1D convolutional context-aware architectures for acoustic sensing and recognition of passing vehicle type

    Publication

    A network architecture that may be employed to sensing and recognition of a type of vehicle on the basis of audio recordings made in the proximity of a road is proposed in the paper. The analyzed road traffic consists of both passenger cars and heavier vehicles. Excerpts from recordings that do not contain vehicles passing sounds are also taken into account and marked as ones containing silence....

  • Vehicle detector training with minimal supervision

    Publication

    - Year 2019

    Recently many efficient object detectors based on convolutional neural networks (CNN) have been developed and they achieved impressive performance on many computer vision tasks. However, in order to achieve practical results, CNNs require really large annotated datasets for training. While many such databases are available, many of them can only be used for research purposes. Also some problems exist where such datasets are not...