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Found 10 results

  1. Hello, and thank you for your help and interest. I have collected from Big Brook in the past, but this time I was finding items of similar composition in the same general area of the stream bed. There had been recent heavy rainfall and the stream bed seemed layered differently. I have been tricked before, and could be getting tricked again, because after a while I trick myself into thinking everything is a fossil. After reading "When Dinosaurs Roamed New Jersey," I went back to Monmouth County with a renewed excitement. Any help you could provide would be greatly appreciated if any of these specimens could be fossils. I placed the numbers under the specimens, and a standard ruler at the bottom, hoping that could assist. I changed the angles of the specimens. Thank you for your time and have a nice day! Bill
  2. I was at Ramanessin Brook yesterday 6/19/21 and met rather friendly and well informed Jeffrey P from fossil forum. Right after we parted I found this bone that reminds me of a mammal phalange of more recent times than the Cretaceous. Can anyone identify its previous owner and when they lived?
  3. Hello everyone! Bergenhoek here! I'm new to the forum, and also to fossil hunting in general. I'm mostly interested in archaeology, but my friends, @Trevor and @The Jersey Devil have a lot more experience than me and they took me along on a trip with them. It was perfect weather too. Although it was in the low 70's, the shade and cool water made for excellent conditions for a casual day of hunting. It was the day after I graduated college, so it was nice to spend my first day as a free man searching the riverbeds for fossils. The goal of the trip for me was to escape my dorm room rather than find anything, but I did find some cool things! The first is part of a jawbone from Enchodus sp. Second are some relatively intact goblin shark teeth The next two pictures are part of a tooth from a mosasaur (crazy how I found it on my second ever trip!) Next is just an interesting piece of pottery I found, I really wanted to find an arrowhead but this'll do Next is a Selachian vertebra The last are some shark teeth I found more things, mostly pieces of shark teeth, but that's it. Enjoy! And some scenery from the site:
  4. JoetheJerseyGuy

    Tooth - Big Brook NJ

    Found in Big Brook, NJ (USA). Picture might not show it but not cracked or fragmented. Enamel (front , tip & sides) is complete except in rear top looks worn. Enchodus Tooth ?
  5. Hi everyone, found this in a new jersey cretaceous creek. Looks like a partial enamel something but I'm not exactly sure what it can possibly be from, it interestingly has some very defined ridges on the least worn side. Very hard to catch the clearest pics to show the sharpest definition but I tried to get the best I could. Maybe this can be a clue to a potential id. Pictures of it with whiteish background are upside down.
  6. Out of the countless New Jersey cretaceous crab claws I've seen and found this has to be one of the strangest claw partials yet. Seems to be an ornamented shell as apposed to the smooth claw textures that are typically found. Definitely a very interesting piece, anyone have any ideas on a possible species or if any ornamental crabs have found in nj cretaceous, or any other new jersey cretaceous hunters ever come across one similar? Definitely a head scratcher
  7. Kurufossils

    Large NJ Cretaceous Bone

    Found this thick bone piece in a new jersey cretaceous creek and wonder if its possible to maybe id since one side has a distinct rough texture while the other is flatter and striated, I would guess either large turtle, mosasaur, or dinosaur. My friend joked its a theropod maxilary skull fragment, but we all know around here that material seems close to impossible to come across haha. Interested to hear any other thoughts.
  8. Kurufossils

    Mystery Cretaceous Tooth New Jersey NJ

    Hello everyone, found this mysterious tooth in a cretaceous stream in New Jersey. Haven't come across any similar or anything I can really compare it to, plus its kinda worn. Which doesn't help but the leaf-like shape alone is very interesting, hopefully this one can be figured out.
  9. Kurufossils

    New Jersey Cretaceous Turtle Bone?

    Hello everyone, I found this bone while on a hunt in the cretaceous creeks of new jersey, very odd bone and definitely feels fossilized. My best guess is turtle but I am very unsure, I appreciate any feedback on this piece if it is Id'able thank you.
  10. Hello Fellow Forum-Goers, Lately I have been somewhat inactive on the forum, and also have not had the opportunity to go fossil hunting in New Jersey since I am at college. But those things do not deter me though. I am here today to tell you about a project I have been doing with fossil classification, specifically classification of some fossil species from the Cretaceous of New Jersey. The goal is to be able to give my computer of a fossil and have it tell me with a certain degree of confidence the probability that it is any one of several New Jersey Cretaceous fossil species. For this project, I began by taking photos of some of my fossils. Here are some examples of the what the photos looked like: Anomoeodus phaseolus Ischyodus bifurcatus Brachyrhizodus wichitaensis The data consisted of around 150 photos, spanning across 6 fossil species. Not represented in the photos above were: Belemnitella americana Enchodus petrosus Ischyrhiza mira To later label this data, I wrote a csv file with labels. From the contents of this file, you can see how many of each specie there were. Note how the common name for these species are used as the labels. id,species IMG_4749,Belemnite-1 IMG_4780,Belemnite-2 IMG_4812,Ray-1 IMG_4813,Ray-2 IMG_4814,Ray-3 IMG_4815,Ray-4 IMG_4816,Ray-5 IMG_4817,Ray-6 IMG_4818,Ray-7 IMG_4819,Ray-8 IMG_4820,Ray-9 IMG_4821,Ray-10 IMG_4822,Ray-11 IMG_4823,Ray-12 IMG_4824,Ray-13 IMG_4825,Ray-14 IMG_4826,Ray-15 IMG_4827,Ray-16 IMG_4828,Ray-17 IMG_4829,Ray-18 IMG_4830,Ray-19 IMG_4831,Ray-20 IMG_4832,Ray-21 IMG_4833,Ray-22 IMG_4834,Ratfish-1 IMG_4835,Ratfish-2 IMG_4836,Ratfish-3 IMG_4837,Ratfish-4 IMG_4838,Ratfish-5 IMG_4839,Ratfish-6 IMG_4840,Ratfish-7 IMG_4841,Ratfish-8 IMG_4842,Ratfish-9 IMG_4843,Ratfish-10 IMG_4844,Ratfish-11 IMG_4845,Ratfish-12 IMG_4846,Ratfish-13 IMG_4847,Ratfish-14 IMG_4848,Ratfish-15 IMG_4849,Ratfish-16 IMG_4850,Ratfish-17 IMG_4851,Ratfish-18 IMG_4852,Ratfish-19 IMG_4853,Ratfish-20 IMG_4854,Ratfish-21 IMG_4855,Ratfish-22 IMG_4856,Ratfish-23 IMG_4857,Ratfish-24 IMG_4858,Ratfish-25 IMG_4859,Ratfish-26 IMG_4860,Ratfish-27 IMG_4861,Ratfish-28 IMG_4862,Ratfish-29 IMG_4863,Ratfish-30 IMG_4864,Ratfish-31 IMG_4865,Ratfish-32 IMG_4866,Ratfish-33 IMG_4867,Ratfish-34 IMG_4868,Enchodus-1 IMG_4869,Enchodus-2 IMG_4870,Enchodus-3 IMG_4871,Enchodus-4 IMG_4872,Enchodus-5 IMG_4873,Enchodus-6 IMG_4875,Enchodus-7 IMG_4876,Enchodus-8 IMG_4877,Enchodus-9 IMG_4878,Enchodus-10 IMG_4879,Enchodus-11 IMG_4888,Enchodus-12 IMG_4889,Enchodus-13 IMG_4890,Enchodus-14 IMG_4891,Enchodus-15 IMG_4892,Enchodus-16 IMG_4903,Pychodont-1 IMG_4905,Pychodont-2 IMG_4906,Pychodont-3 IMG_4907,Pychodont-4 IMG_4908,Pychodont-5 IMG_4909,Pychodont-6 IMG_4910,Pychodont-7 IMG_4911,Pychodont-8 Now, with the labels and data. I began to make a program that fed in the images and then used Keras ( a machine learning library that has the tools for something called a convolutional neural network) in the programming language Python. Here is the beginning of the code: import numpy <- This gets me NumPy, which allows for easy use of vectors and matrices to work with data import collections <- This allows me to make better data structures called "dictionaries" import os <- This allows me to get the path of the image in my computer import imageio <- This allows me to write edited images to other folders from PIL import Image <- This allows me to manipulate the images, in way such as flipping or rotating. from random import shuffle <- This allows me to randomly shuffle the training data. This code puts each fossil image and its label into something like a container together, this "container" is called a dictionary species_dictionary = collections.OrderedDict() our_file = open("fossil_labels.csv","r") file_contents = our_file.read() file_contents = file_contents.split('\n') for iteration in range(1,len(file_contents)): file_contents[iteration] = file_contents[iteration].split(',') species_dictionary[file_contents[iteration][0]] = file_contents[iteration][1] I will skip the other code and now discuss convolutional neural networks, which are used in image classification So, right now I have all the fossil image with their label. The network can now use these to find clusters of pixels in a given photos that correspond to a particular fossil species. Overtime, the network letters that this or that cluster of pixels is common to one a single fossil species. Then, it can recognize that cluster in a new or novel image that it has not been trained on. Here are the convolutional layers: model = Sequential() model.add(Conv2D(32, kernel_size = (3, 3), activation='relu', input_shape=(IMG_SIZE, IMG_SIZE, 1))) model.add(MaxPooling2D(pool_size=(2,2))) model.add(BatchNormalization()) model.add(Conv2D(64, kernel_size=(3,3), activation='relu')) model.add(MaxPooling2D(pool_size=(2,2))) model.add(BatchNormalization()) model.add(Conv2D(64, kernel_size=(3,3), activation='relu')) model.add(MaxPooling2D(pool_size=(2,2))) model.add(BatchNormalization()) model.add(Conv2D(96, kernel_size=(3,3), activation='relu')) model.add(MaxPooling2D(pool_size=(2,2))) model.add(BatchNormalization()) model.add(Conv2D(32, kernel_size=(3,3), activation='relu')) model.add(MaxPooling2D(pool_size=(2,2))) model.add(BatchNormalization()) model.add(Dropout(0.2)) model.add(Flatten()) model.add(Dense(128, activation='relu')) model.add(Dense(5, activation = 'softmax')) model.compile(loss='binary_crossentropy', optimizer='adam', metrics = ['accuracy']) model.fit(training_images, training_labels, batch_size = 50, epochs = 10, verbose = 1) I do not expect this code to be fully understood.The network uses weights or sensitivities to different pixel clusters. Then as it learns how its predictions for a photo compares to the actual training photo I gave it, it updates the weights to reflect this. By the end this "error loss" should reach towards 0, and when it does, we know that its predictions correspond very close with the actual photo, now allowing it to classify fossil images for these six species well. If it were training on 10 species it would classify all 10 well. Here is the output of the training: # Epoch 1/10 # 164/164 [==============================] - 497s 3s/step - loss: 0.3975 - acc: 0.8329 # Epoch 2/10 # 164/164 [==============================] - 139s 846ms/step - loss: 0.1026 - acc: 0.9610 # Epoch 3/10 # 164/164 [==============================] - 139s 848ms/step - loss: 0.0427 - acc: 0.9902 # Epoch 4/10 # 164/164 [==============================] - 126s 771ms/step - loss: 0.0232 - acc: 0.9939 # Epoch 5/10 # 164/164 [==============================] - 119s 728ms/step - loss: 0.0153 - acc: 0.9963 # Epoch 6/10 # 164/164 [==============================] - 2258s 14s/step - loss: 0.0066 - acc: 0.9976 # Epoch 7/10 # 164/164 [==============================] - 141s 861ms/step - loss: 0.0047 - acc: 1.0000 # Epoch 8/10 # 164/164 [==============================] - 135s 824ms/step - loss: 0.0048 - acc: 1.0000 # Epoch 9/10 # 164/164 [==============================] - 132s 803ms/step - loss: 0.0027 - acc: 1.0000 # Epoch 10/10 # 164/164 [==============================] - 122s 746ms/step - loss: 0.0043 - acc: 1.0000 You can see that the loss keeps going down with more and more training. For the future, I definitely need to take more photos to get more data and allow it to train on a graphical processing unit (GPU) as opposed to the normal CPU that you use on a laptop. The GPU is better at parallel processing and can train the network in seconds (on my computer it took 15 minutes). Well that is the current state of the project. I still need to do more but thank you for staying here till the end. I hope you have a nice day. -Trevor
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