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1

Utilizing satellite and UAV data for crop yield prediction and monitoring through deep learning

Mathivanan Sandeep Kumar, Jayagopal Prabhu

Acta Geophysica

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2022

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Vol. 70, no 6

2991--3004

EN

Agriculture is sighted more use cases of drones, and with the expanding population, food yields are becoming more well organized. Drones are used in examining crops and exploiting data to determine what requires greater attention. This research study focuses on how deep learning (DL) has been used with drone technology to create solutions for detecting crop fields within a certain regions of interest (ROI). Extracting images from a drone and analysing them with a DL system to identify crop fields and yields for less-developed nations are solution to a prevalent challenge that land use–land cover (LULC) encounters. The limitations of drone spot-checking in the context of agricultural fields and the constraints of utilizing DL to detect yields. Also, a novel method is offered for detecting and tracking crop fields using a single camera on our UAV. The estimated background movements using a perspective transformation model given a sequence of video frames and then locate distinct locations in the background removed picture to detect moving objects. The optical flow matching is used to determine the spatiotemporal features of each moving item and then categorize our targets, which have considerably different motions than the backdrop. Kalman filter tracking has used to ensure that our detections are consistent across time. The hybrid crop field detection model is to evaluate on real uncrewed aerial vehicle (UAV) recordings. And the findings suggest that hybrid crop field detection successfully detects and tracks crop fields through tiny UAV’s with low computational resources. A crop field module, which aids in reconstruction quality evaluation by cropping specific ROIs from the whole field, and a reversing module, which projects ROIs-Vellore to relative raw pictures, are included in the proposed method. The results exhibit faster identification of cropping and reversing modules, impacting ROI height selection and reverse extraction of ROI location from raw pictures.

2

Zapytania wzorca do trajektoryjnej hurtowni danych

Gorawski M., Jureczek P.

Studia Informatica

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2009

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Vol. 30, nr 2A

317-328

PL

Artykuł podejmuje temat zapytań wzorca dla Trajektoryjnej Hurtowni Danych, TrDW. W ramach zapytań wzorca został zaprezentowany sposób przekształcania trajektorii obiektów do postaci sekwencji regionów oraz eksploracji tak uzyskanych sekwencji z użyciem funkcji porównujących. Przedstawione funkcje porównujące zostały podzielone na dwie grupy. Pierwsza grupa umożliwia uzyskanie informacji na temat konkretnego, zdefiniowanego przez użytkownika wzorca. Druga natomiast służy pozyskiwaniu informacji podsumowujących dotyczących wszystkich analizowanych sekwencji trajektorii. Informacje uzyskane w wyniku użycia drugiej grupy mogą również posłużyć, jako dane wejściowe grupy pierwszej. W artykule przedstawiono również wpływ różnych parametrów, wykorzystywanych podczas przekształcania trajektorii, na rozmiar składowanych agregatów.

EN

This paper presents the query model for Trajectory Data Warehouse. The pattern queries in this paper present a way of transforming object trajectories into region sequences, as well as exploring such sequences using comparison methods. Such comparison methods are divided into two groups. The first group makes it possible to collect information about a particular user-defined pattern. The second involves obtaining information summary of all analyzed trajectory sequences. Information obtained as a result of using the second group may be also used as input data for the first group. We also show the impact of different parameters of transformation of trajectories on the size of stored aggregates.

3

FPGA implementation of a lossless to lossy bitonal image compression system

Savakis A., Lukowiak M., Pyle J.

Electronics and Telecommunications Quarterly

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2008

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Vol. 54, No 4

533-546

EN

This paper presents an FPGA implementation of a lossless to lossy image compression system that incorporates region of interest processing. Block Arithmetic Coder Image Compression is combined with Low-Latency Greedy Flipping Utilizing Forgetful Error Diffusion for loss introduction. The approach allows for perfect quality, associated with lossless compression, or three levels of reduced image quality, high, medium and low, associated with various levels of loss introduction. Region of interest processing can be incorporated by adjusting the system parameters for maximum visual benefit. The overall system was successfully realized on a Virtex FPGA platform.

4

Interactive image browsing with JPEG2000 Internet Protocol

Saganowski Ł.

Przegląd Elektrotechniczny

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2006

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R. 82, nr 1

58-62

EN

JPEG2000 Internet Protocol (JPIP) and JPEG2000 give powerful and flexible client/server architecture that takes advantage of efficient compression and existing internet protocols. We can store only one compressed file at the server side and transmit image to the client. At the client side user can select quality, Region of Interest (ROI) of the image. These operations do not require to transmit or decode entire codestream. Only specific data connected with ROI or quality level are transmitted to the client. This minimizes server computational burden, storage and bandwidth.

PL

JPEG2000 Internet Protocol (JPIP) razem z kompresją JPEG2000 tworzą wydajny i elastyczny system typu klient/serwer czerpiący korzyści z wydajnego systemu kompresji oraz istniejących protokołów internetowych. Po stronie serwera możemy zapisać tylko jeden skompresowany obraz. Po stronie klienta wybieramy jakość przesyłanego obrazu lub obszar zainteresowania w obrazie - Region of Interest ROI.

5

Gaze-J2K: gaze-influenced image coding using eye trackers and JPEG 2000

Nguyen A., Chandran V., Sridharan S.

Journal of Telecommunications and Information Technology

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2006

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nr 1

3-10

EN

The use of visual content in applications of the digital computer has increased dramatically with the advent of the Internet and world wide web. Image coding standards such as JPEG 2000 have been developed to provide scalable and progressive compression of imagery. Advances in image and video analysis are also making human-computer interaction multi-modal rather than through the use of a keyboard or mouse. An eye tracker is an example input device that can be used by an application that displays visual content to adapt to the viewer. Many features are required of the format to facilitate this adaptation, and some are already part of image coding standards such as JPEG 2000. This paper presents a system incorporating the use of eye tracking and JPEG 2000, called Gaze-J2K, to allow a customised encoding of an image by using a user's gaze pattern. The gaze pattern is used to automatically determine and assign importance to fixated regions in an image, and subsequently constrain the encoding of the image to these regions.