Apple detection during different growth stages in orchards using the improved YOLO-V3 model

A review on weed detection using ground-based machine vision and image processing techniques

Evaluation of support vector machine and artificial neural networks in weed detection using shape features

Machine vision for precision agriculture has attracted considerable research interest in recent years. The aim of this paper is to review the most recent work in the application of machine vision to agriculture, mainly for crop farming. This study can serve as a research guide for the researcher and practitioner alike in applying cognitive technology to agriculture. Studies of different agricultural activities that support crop harvesting are reviewed, such as fruit grading, fruit counting, and yield estimation. Moreover, plant health monitoring approaches are addressed, including weed, insect, and disease detection. Finally, recent research efforts considering vehicle guidance systems and agricultural harvesting robots are also reviewed.

Machine Vision Systems in Precision Agriculture for Crop Farming

A survey of deep learning techniques for weed detection from images

Automatic crop detection under field conditions using the HSV colour space and morphological operations

Improved image processing-based crop detection using Kalman filtering and the Hungarian algorithm

Background It is known that proteins associated with Alzheimer's disease (AD) pathogenesis are significantly reduced by 40 Hz entrainment in mice. If this were to translate to humans, verifying that such a light stimulus can induce a 40 Hz entrainment response in humans and harnessing insights from these case studies could be one step in the development of a multisensory device to prevent and treat AD. Objective Verify the inducement of a 40 Hz response in the human brain by a 40 Hz light stimulus and obtain insights that could potentially aid in the development of a multisensory device for the prevention and treatment of AD. Methods Electroencephalographic brain activity was recorded simultaneously with application of stimulus at different frequencies and intensities. Power spectral densities were analyzed. Results Entrainment to visual stimuli occurred with the largest response at 40 Hz. The high intensity 40 Hz stimulus caused widespread entrainment. The number of electrodes demonstrating entrainment increased with increasing light intensity. Largest amplitudes for the high intensity 40 Hz stimulus were consistently found at the primary visual cortex. There was a harmonic effect at double the frequency for the 40 Hz stimulus. An eyes-open protocol caused more entrainment than an eyes-closed protocol. Conclusion It was possible to induce widespread entrainment using a 40 Hz light stimulus in this sample cohort. Insights gleaned from these case studies could potentially aid in the development of a multisensory medical device to prevent and treat AD.

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Gamma Band Light Stimulation in Human Case Studies: Groundwork for Potential Alzheimer's Disease Treatment.

This paper describes a scalable and extendable Remote Field Programmable Gate Array Laboratory (Remote FPGA) which can be used to enhance the learning of digital systems and FPGA applications. The web-based console provides an always-on, real-time, interactive control and visualisation interface to/from a bank of remote FPGAs. A Xilinx ISE project template enables integration of user HDL-based designs to execute on the Remote FPGA. Host-FPGA communication is supported using a register-based interface. Users can create real-time, interactive and visual demonstrators of digital systems components. The paper presents a demonstrator for a Finite State Machine (FSM) application, and illustrates the use of web-based control and visualisation for enhanced learning of FSM behaviour. The paper also presents a case study of the use of Remote FPGA in undergraduate teaching.

Remote FPGA Lab with Interactive Control and Visualisation Interface

This paper outlines a scheme for compressing EEG signals based on the JPEG2000 image compression algorithm. Such a scheme could be used to compress signals in an ambulatory system, where low-power operation is important to conserve battery life; therefore, a high compression ratio is desirable to reduce the amount of data that needs to be transmitted. The JPEG2000 specification makes use of the wavelet transform, which can be efficiently implemented in embedded systems. The standard was broken down to its core components and adapted for use on EEG signals with additional compression steps added. Variations on the components were tested to maximize compression ratio (CR) while maintaining a low percentage root-mean-squared difference (PRD) and minimize power requirements. Initial tests indicate that the algorithm performs well in relation to other EEG compression methods proposed in the literature.

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Brian Mc Ginley

Papers

Automatic crop detection under field conditions using the HSV colour space and morphological operations

Improved image processing-based crop detection using Kalman filtering and the Hungarian algorithm

Gamma Band Light Stimulation in Human Case Studies: Groundwork for Potential Alzheimer's Disease Treatment.

Remote FPGA Lab with Interactive Control and Visualisation Interface

Low power compression of EEG signals using JPEG2000