Selecting visually overlapping image pairs without any prior information is an essential task of large-scale structure from motion (SfM) pipelines. To address this problem, many state-of-the-art ...image retrieval systems adopt the idea of bag of visual words (BoVW) for computing image-pair similarity. In this paper, we present a method for improving the image pair selection using BoVW. Our method combines a conventional vector-based approach and a set-based approach. For the set similarity, we introduce a modified version of the Simpson (m-Simpson) coefficient. We show the advantage of this measure over three typical set similarity measures and demonstrate that the combination of vector similarity and the m-Simpson coefficient effectively reduces false positives and increases accuracy. To discuss the choice of vocabulary construction, we prepared both a sampled vocabulary on an evaluation dataset and a basic pre-trained vocabulary on a training dataset. In addition, we tested our method on vocabularies of different sizes. Our experimental results show that the proposed method dramatically improves precision scores especially on the sampled vocabulary and performs better than the state-of-the-art methods that use pre-trained vocabularies. We further introduce a method to determine the k value of top-k relevant searches for each image and show that it obtains higher precision at the same recall.
To expand the use of systems using a camera on portable devices such as tablets and smartphones, we have developed and propose a memory saving feature descriptor, the use of which is one of the ...essential techniques in computer vision. The proposed descriptor compares pixel values of pre-fixed positions in the small patch around the feature point and stores binary values. Like the conventional descriptors, it extracts the patch on the basis of the scale and orientation of the feature point. For memories of the same size, it achieves higher accuracy than ORB and BRISK in all cases and AKAZE for the images with textured regions.
Based on the appearance of tomatoes, it is possible to determine whether they are diseased. Detecting diseases early can help the yield losses of tomatoes through timely treatment. However, human ...visual inspection is expensive in terms of the time and labor required. This paper presents an automatic tomato disease monitoring system using modular and extendable mobile robot we developed in a greenhouse. Our system automatically monitors whether tomatoes are diseased and conveys the specific locations of diseased tomatoes to users based on the location information of the image data collected by the robot, such that users can adopt timely treatment. This system consists of two main parts: a modular, extendable mobile robot that we developed and a server that runs a tomato disease detection program. Our robot is designed to be configured and extended according to the actual height of the tomato vines, thus ensuring that the monitoring range covers most tomatoes. It runs autonomously between two rows of tomato plants and collects the image data. In addition to storing the image data of tomatoes, the data server runs a program for detecting diseases. This program contains a two-level disease detection model: a detection network for detecting diseased tomatoes and a validation network for verifying the detection results. The validation network verifies the results of the detection network by classifying the outputs of the detection network, thus reducing the false positive rate of the proposed system. Experimentally, this work focuses on the blossom-end rot of tomatoes. In this paper, YOLOv5, YOLOv7, Faster R-CNN, and RetinaNet are trained and compared on datasets divided by different conditions. YOLOv5l showed the best results on the randomly divided dataset: the mAP@0.5 reached 90.4%, and the recall reached 85.2%. Through the trained YOLOv5l, a dataset was created for training the classification networks: ResNet, MobileNet, and DenseNet. MobileNetv2 achieved the best overall performance with a 96.7% accuracy and a size of 8.8 MB. The final deployment to the system included YOLOv5l and MobileNetv2. When the confidence threshold of YOLOv5l was set to 0.1, the two-level model’s false positive and false negative rates were 13.3% and 15.2%, respectively. Compared to using YOLOv5l alone, the false positive rate decreased by 5.7% and the false negative rate increased by only 2.3%. The results of the actual operation of the proposed system reveal that the system can inform the user of the locations of diseased tomatoes with a low rate of false positives and false negatives, and that it is an effective and promotable approach.
In recent years, Japan’s agricultural industry has faced a number of challenges, including a decline in production due to a decrease in farmland area, a shortage of labor due to a decrease in the ...number of producers, and an aging population. Therefore, in recent years, smart agriculture using robots and IoT has been studied. A caliper is often used to analyze the growth of tomatoes in a plant factory, but this method may damage the stems and is also hard on the measurer. We developed a system that detects them through image analysis and measures the thickness of stems and the length between flower clusters and growing points. The camera device developed in this study costs about USD 150 and once installed, it does not need to be moved unless it malfunctions. The camera device reduces the effort required to analyze crop growth by about 80%.
Classification of school violence has been proven to be an effective solution for preventing violence within educational institutions. As a result, technical proposals aimed at enhancing the efficacy ...of violence classification are of considerable interest to researchers. This study explores the utilization of the SORT tracking method for localizing and tracking objects in videos related to school violence, coupled with the application of LSTM and GRU methods to enhance the accuracy of the violence classification model. Furthermore, we introduce the concept of a padding box to localize, identify actions, and recover tracked objects lost during video playback. The integration of these techniques offers a robust and efficient system for analyzing and preventing violence in educational environments. The results demonstrate that object localization and recovery algorithms yield improved violent classification outcomes compared to both the SORT tracking and violence classification algorithms alone, achieving an impressive accuracy rate of 72.13%. These experimental findings hold promise, especially in educational settings, where the assumption of camera stability is justifiable. This distinction is crucial due to the unique characteristics of violence in educational environments, setting it apart from other forms of violence.
We present a new approach for selecting image pairs that are more likely to match in Structure from Motion (SfM). We propose to use Jaccard Similarity (JacS) which shows how many different visual ...words is shared by an image pair. In our method, the similarity between images is evaluated using JacS of bag-of-visual-words in addition to tf-idf (term frequency-inverse document frequency), which is popular for this purpose. To evaluate the efficiency of our method, we carry out experiments on our original datasets as well as on “Pantheon” dataset, which is derived from Flickr. The result of our method using both JacS and tf-idf is better than the results of a standard method using tf-idf only.
In the current study we investigated the antibacterial activity of fragrance ingredients against Legionella pneumophila, a causative agent of severe pneumonia. Among the 41 different fragrance ...ingredients tested, we found that the natural fragrance ingredients oakmoss (OM) and birch tar oil (BT), which contain many components, exhibit potent antibacterial activity. The minimum inhibitory concentration (MIC, % (v/v)) of OM and BT were 0.0020 and 0.0024, respectively and were lower than that of cinnamic aldehyde (0.0078), which has been previously shown to possess high antimicrobial activity. In a time–kill assay of OM and BT at MIC and two times MIC, the colony forming units (CFU) of the microbe were reduced to between 10−3 to 10−4 of the original CFU after 1 h co-incubation. After this time, the CFU gradually decreased in number, but remained above detection levels even after a 48-h co-incubation, except for BT at two times MIC. In contrast, at a concentration of 0.1% OM and BT (approximately 50 times MIC), CFU were not detected after co-incubation for 1 h. Another 18 fragrance ingredients including ketone, aldehyde, lactone, acid, phenol derivative, aliphatic alcohol and quinoline also exhibited a lesser degree of antibacterial activity against L. pneumophila at a MIC of less than 0.10.
This paper presents a method for segmenting a 3D point cloud into planar surfaces using recently obtained discretegeometry results. In discrete geometry, a discrete plane is defined as a set of grid ...points lying between two parallel planes with a small distance, called thickness. In contrast to the continuous case, there exist a finite number of local geometric patterns （LGPs） appearing on discrete planes. Moreover, such an LGP does not possess the unique normal vector but a set of normal vectors. By using those LGP properties, we first reject non-linear points from a point cloud, and then classify non-rejected points whose LGPs have common normal vectors into a planar-surface-point set. From each segmented point set, we also estimate the values of parameters of a discrete plane by minimizing its thickness.
The time for diabetic nephropathy (DN) to progress from mild to severe is long. Thus, methods to continuously repress DN are required to exert long-lasting effects mediated through epigenetic ...regulation. In this study, we demonstrated the ability of nicotinamide adenine dinucleotide (NAD) and its metabolites to reduce albuminuria through Sirt1- or Nampt-dependent epigenetic regulation. We previously reported that proximal tubular Sirt1 was lowered before glomerular Sirt1. Repressed glomerular Sirt1 was found to epigenetically elevate Claudin-1. In addition, we reported that proximal tubular Nampt deficiency epigenetically augmented TIMP-1 levels in Sirt6-mediated pathways, leading to type-IV collagen deposition and diabetic fibrosis. Altogether, we propose that the Sirt1/Claudin-1 axis may be crucial in the onset of albuminuria at the early stages of DN and that the Nampt/Sirt6/TIMP-1 axis promotes diabetic fibrosis in the middle to late stages of DN. Finally, administration of NMN, an NAD precursor, epigenetically potentiates the regression of the onset of DN to maintain Sirt1 and repress Claudin-1 in podocytes, suggesting the potential use of NAD metabolites as epigenetic medications for DN.
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